{"id": "resource_arcashla_extract_1", "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": "samplesheet_arch_bulk_rnaseq_se_0_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": "Which columns should the input samplesheet have for: Single-end Illumina RNA-seq with strandedness?", "criteria": {"sample,bam": null, "sample,vcf": null, "sample,fastq_1": null, "sample,fastq_1,strandedness": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 3}
{"id": "pipe_all101_cageseq_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for cage analysis? Specific context: 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": {"cageseq": "CAGE-sequencing analysis pipeline with trimming, alignment and counting of CAGE tags. [cage, cage-seq, cageseq-data]", "demo": "nf-core/demo is a simple nf-core style bioinformatics pipeline for workshops and demos. [demo, minimal-example, training", "cutandrun": "Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak callin", "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]"}}, "target": "cageseq", "target_idx": 0}
{"id": "schema_std_sopa_2_0", "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,sample_id,fastq_1,fastq_2,method": null, "sample,run,group,short_reads_1,short_reads_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,id,data_path,fastq_dir,cytaimage": null}}, "target": "sample,id,data_path,fastq_dir,cytaimage", "target_idx": 3}
{"id": "resource_bedtools_intersect_5", "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_single": null, "process_high": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_bcl2fastq_3", "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_single": null, "process_long": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_bam_tumor_normal_somatic_variant_calling_gatk_1", "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": {"gatk4_baserecalibrator": null, "umitools_dedup": null, "gatk4_asereadcounter": null, "bam_tumor_normal_somatic_variant_calling_gatk": null, "ivar_variants": null}}, "target": "bam_tumor_normal_somatic_variant_calling_gatk", "target_idx": 3}
{"id": "qc_adapt_singlecell_multiqc_0_48", "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_dynamic_resource_allocation_3", "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_genmod_score_0", "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": {"refsolver/score": "Score a query sequence dictionary against a reference using ref-solver", "malt/run": "MALT, an acronym for MEGAN alignment tool, is a sequence alignment and analysis tool designed for processing h", "openms/decoydatabase": "Create a decoy peptide database from a standard FASTA database.", "genmod/annotate": "for annotating regions, frequencies, cadd scores", "genmod/score": "Score the variants of a vcf based on their annotation"}}, "target": "genmod/score", "target_idx": 4}
{"id": "qc_adapt_pacbio_hifi_2_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": "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_methylseq_bisulfite_0_2", "category": "samplesheet_schema", "state": {"assay": "Whole-Genome Bisulfite Sequencing (WGBS / EM-seq)", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Whole-Genome Bisulfite Sequencing (WGBS / EM-seq)?", "criteria": {"sample,vcf": null, "sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "resource_bamaligncleaner_1", "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_long": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "field_constraint_sample_2_4", "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": "qc_adapt_bulk_multiqc_2_40", "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_samtools_addreplacerg_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Adds or replaces read group (RG) tags in BAM/CRAM/SAM files (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gmmdemux": "GMM-Demux is a Gaussian-Mixture-Model-based software for processing sample barcoding data (cell hashing and MU", "atlas/splitmerge": "split single end read groups by length and merge paired end reads", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "manta/tumoronly": "Manta calls structural variants (SVs) and indels from mapped paired-end sequencing reads. It is optimized for ", "samtools/addreplacerg": "Adds or replaces read group (RG) tags in BAM/CRAM/SAM files"}}, "target": "samtools/addreplacerg", "target_idx": 4}
{"id": "field_constraint_phenotype_3_6", "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, "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": "mod_kallistobustools_ref_0", "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": {"kallistobustools/ref": "index creation for kb count quantification of single-cell data.", "samplesheetparser/validate": "Validate an Illumina SampleSheet.csv (V1 or V2) for index, adapter, and\nstructural issues. Format is auto-dete", "cellbender/removebackground": "Module to use CellBender to estimate ambient RNA from single-cell RNA-seq data", "scvitools/scar": "Module to use scAR to remove ambient RNA from single-cell RNA-seq data", "binette": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning"}}, "target": "kallistobustools/ref", "target_idx": 0}
{"id": "field_constraint_expected_cells_3_8", "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, "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": "samplesheet_arch_cfdna_liquid_biopsy_6_5", "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 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, "sample,timepoint,fastq": null, "sample,bam": null}}, "target": "patient,sample,timepoint,volume_ml,fastq_1,fastq_2", "target_idx": 1}
{"id": "qc_adapt_singlecell_multiqc_2_16", "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": "resource_bedtools_getfasta_1", "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_long": null, "process_high": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_spatial_visium_3_1", "category": "samplesheet_schema", "state": {"assay": "10x Visium spatial transcriptomics with histology image", "first_step": "FASTQC", "template": "nf-core/spatialaxe"}, "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,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_ampliseq_its_fungal_1_5", "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 samplesheet have for Fungal ITS1/ITS2 marker gene amplicon surveillance?", "criteria": {"sample,bam": 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": "mod_bedtools_closest_1", "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": {"chromap_index": "Indexes a fasta reference genome ready for chromatin profiling.", "gatk4_haplotypecaller": "Call germline SNPs and indels via local re-assembly of haplotypes", "bedtools_coverage": "computes both the depth and breadth of coverage of features in file B on the features in file A", "bedtools_groupby": "Groups features in a BED file by given column(s) and computes summary statistics for each group to another col", "bedtools_closest": "For each feature in A, finds the closest feature (upstream or downstream) in B."}}, "target": "bedtools_closest", "target_idx": 4}
{"id": "samplesheet_arch_cutandrun_pe_0_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: CUT&RUN / CUT&TAG chromatin profiling with IgG control?", "criteria": {"sample,bam": 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": "samplesheet_arch_vcf_annotation_pipeline_1_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": "Which columns should the 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": "samplesheet_arch_viral_ont_single_8_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 are standard for viral amplicon sequencing?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null, "sample,fasta": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "qc_adapt_ont_nanoplot_2_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": "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_singlecell_multiqc_2_42", "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_fastqscreen_fastqscreen_1", "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", "fgumi_dedup": "Mark or remove PCR duplicates using UMI information with fgumi", "biscuit_mergecg": "Merges methylation information for opposite-strand C's in a CpG context", "ampcombi2_cluster": "A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete usin", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files."}}, "target": "fastqscreen_fastqscreen", "target_idx": 0}
{"id": "mod_deeptools_plotpca_0", "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": {"shinyngs/staticexploratory": "Make exploratory plots for analysis of matrix data, including PCA, Boxplots and density plots", "last/lastal": "Aligns query sequences to target sequences indexed with lastdb", "savana/classify": "Classify structural variants using SAVANA", "deeptools/plotpca": "Generates principal component analysis (PCA) plot using a compressed matrix generated by multibamsummary or mu", "plink2/pca": "Perform PCA analysis using PLINK"}}, "target": "deeptools/plotpca", "target_idx": 3}
{"id": "mod_pairtools_split_1", "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": {"seqkit_fq2fa": null, "pairtools_split": null, "atlas_splitmerge": null, "bcftools_merge": null, "bamtools_split": null}}, "target": "pairtools_split", "target_idx": 1}
{"id": "qc_adapt_qc_aggregate_0_26", "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_autocycler_compress_1", "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": {"numorph_3dunet": "3DUnet for cell nuclei quantification on 3D microscopy images of the numorph toolkit.", "autocycler_compress": "Package candidate assemblies for clustering by Autocycler.", "autocycler_resolve": "Resolve trimmed assembly graphs into final contigs within Autocycler.", "autocycler_subsample": "Downsample long-read sequencing data to the requested coverage using Autocycler.", "plink2_extract": "Subset plink pfiles with a text file of variant identifiers"}}, "target": "autocycler_compress", "target_idx": 1}
{"id": "pipe_all101_molkart_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for fish. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"fastquorum": "Pipeline to produce consensus reads using unique molecular indexes/barcodes (UMIs) [consensus, umi, umis]", "chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. [chip, chip-seq, chromatin-immunoprecipitation]", "genomeqc": "Compare the quality of multiple genomes, along with their annotations. [genome-assembly-evaluation, genomics, phylogenet", "mcmicro": "An end-to-end processing pipeline that transforms multi-channel whole-slide images into single-cell data. [bioformats, i", "molkart": "A pipeline for processing Molecular Cartography data from Resolve Bioscience (combinatorial FISH) [fish, image-processin"}}, "target": "molkart", "target_idx": 4}
{"id": "subworkflow_pkg_fastq_removeadapters_merge_1", "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": {"Local subworkflow FASTQ_REMOVEADAPTERS_MERGE": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow fastq_removeadapters_merge": null}}, "target": "Use nf-core subworkflow fastq_removeadapters_merge", "target_idx": 3}
{"id": "mod_fcsgx_fetchdb_1", "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": {"trgt_merge": "Merge TRGT VCFs from multiple samples", "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", "bakta_baktadbdownload": "Downloads BAKTA database from Zenodo", "fgbio_copyumifromreadname": "Copies the UMI at the end of a bam files read name to the RX tag."}}, "target": "fcsgx_fetchdb", "target_idx": 2}
{"id": "resource_adapterremovalfixprefix_4", "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_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "schema_std_scnanoseq_0_0", "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,seq_data,pbi,start_from": null, "sample_id,img_directory,parameter_file": null, "sample,fastq,cell_count": null, "sample,fastq_1,fastq_2,bam,seq_type": null}}, "target": "sample,fastq,cell_count", "target_idx": 2}
{"id": "qc_adapt_pe_illumina_fastqc_2_44", "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": "samplesheet_arch_smartseq_plate_based_3_1", "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": "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": {"sample,fastq_1,fastq_2": null, "plate,well,sample,fastq_1,fastq_2": null, "sample,well,fastq": null, "sample,matrix": null}}, "target": "plate,well,sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "intent_prepare_data_22", "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", "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": "prepare_data", "target_idx": 3}
{"id": "mod_modkit_callmods_0", "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": {"modkit/callmods": "Call mods from a modbam, creates a new modbam with probabilities set to 100% if a base modification is called ", "genrich": "Peak-calling for ChIP-seq and ATAC-seq enrichment experiments", "deeptools/plotpca": "Generates principal component analysis (PCA) plot using a compressed matrix generated by multibamsummary or mu", "bismark/report": "Collects bismark alignment reports", "bismark/deduplicate": "Removes alignments to the same position in the genome\nfrom the Bismark mapping output."}}, "target": "modkit/callmods", "target_idx": 0}
{"id": "mod_cnvkit_call_0", "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": {"cnvkit/genemetrics": "Copy number variant detection from high-throughput sequencing data", "pcgr/getref": "Get reference to run Personal Cancer Genome Reporter (PCGR)", "cnvkit/call": "Given segmented log2 ratio estimates (.cns), derive each segment’s absolute integer copy number", "cnvkit/export": "Convert copy number ratio tables (.cnr files) or segments (.cns) to another format.", "bioawk": "Bioawk is an extension to Brian Kernighan's awk, adding the support of several common biological data formats."}}, "target": "cnvkit/call", "target_idx": 2}
{"id": "samplesheet_arch_ont_direct_rna_se_2_0", "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?", "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": "samplesheet_arch_spatial_visium_1_4", "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 10x Visium spatial transcriptomics with histology image?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,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": "samplesheet_arch_pacbio_hifi_wgs_5_5", "category": "samplesheet_schema", "state": {"assay": "Long-read Pacific Biosciences HiFi sequencing", "first_step": "HIFIADAPTERFILT", "template": "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": null, "sample,fastq_1,fastq_2,group": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_0_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 input samplesheet have for: PacBio HiFi unaligned BAM variant calling?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,bam", "target_idx": 0}
{"id": "qc_adapt_ont_ultra_long_2_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": "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": "qc_adapt_pe_illumina_fastqc_2_40", "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": "field_constraint_sample_1_12", "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_merfin_hist_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compare k-mer frequency in reads and assembly to devise the metrics K* and QV* (tools: merfin)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"verifybamid_verifybamid": "Detecting and estimating inter-sample DNA contamination became a crucial quality assessment step to ensure hig", "merfin_hist": "Compare k-mer frequency in reads and assembly to devise the metrics K* and QV*", "abyss_abysspe": "ABySS is a de novo sequence assembler intended for short paired-end reads and genomes of all sizes.", "ffq": "A command line tool that makes it easier to find sequencing data from the SRA / GEO / ENA.", "ale": "ALE: assembly likelihood estimator."}}, "target": "merfin_hist", "target_idx": 1}
{"id": "noul_executor_support_17", "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_annosine_0", "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_high": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_cafe_1", "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": {"cafe": "Analysis of gene family evolution", "controlfreec_freec2circos": "Format Freec output to circos input format", "blast_blastp": "BLASTP (Basic Local Alignment Search Tool- Protein) compares an amino acid (protein) query sequence against a ", "tsebra": "Transcript Selector for BRAKER TSEBRA combines gene predictions by selecting transcripts based on their extris", "atlasgeneannotationmanipulation_gtf2featureannotation": "Generate tables of feature metadata from GTF files"}}, "target": "cafe", "target_idx": 0}
{"id": "mod_fastq_create_umi_consensus_fgbio_0", "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": {"fastq_create_umi_consensus_fgbio": null, "rastair/mbiasparser": null, "fgbio/filterconsensusreads": null, "hmmer/jackhmmer": null, "chelae/trim": null}}, "target": "fastq_create_umi_consensus_fgbio", "target_idx": 0}
{"id": "qc_adapt_pe_illumina_fastqc_2_15", "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_trimal_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: trimAl is a tool for the automated removal of spurious sequences or poorly aligned regions from a multiple sequence alignment. (tools: trimal)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"concoct/extractfastabins": null, "bigslice/bigslice": null, "amps": null, "ashlar": null, "trimal": null}}, "target": "trimal", "target_idx": 4}
{"id": "mod_mmseqs_createtsv_0", "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/createindex": "Creates sequence index for mmseqs database", "mmseqs/createtsv": "Create a tsv file from a query and a target database as well as the result database", "mmseqs/createdb": "Create an MMseqs database from an existing FASTA/Q 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", "plink2/vcf2bgen": "Convert from VCF file to BGEN file version 1.2 format preserving dosages."}}, "target": "mmseqs/createtsv", "target_idx": 1}
{"id": "resource_any2fasta_2", "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_medium": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_smartseq_plate_based_5_3", "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": "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,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": "mod_quantmsutils_mzmlstatistics_1", "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_mzmlstatistics": "Generate statistics from mzML files using quantms-utils", "openms_fileconverter": "Converts between different mass spectrometry file formats (e.g. mzML, mzXML, mgf, mzData, dta, dta2d, featureX", "comet": "Comet is an open source tandem mass spectrometry (MS/MS) sequence database search tool", "eautils_fastqstats": "Calculate general and per-base statistics from FASTQ files", "hpsuissero": "Serotype prediction of Haemophilus parasuis assemblies"}}, "target": "quantmsutils_mzmlstatistics", "target_idx": 0}
{"id": "mod_dragonflye_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Assemble bacterial isolate genomes from Nanopore reads (tools: dragonflye)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"motus_profile": "Taxonomic meta-omics profiling using universal marker genes", "plasmidid": "assembles bacterial plasmids", "hmmcopy_gccounter": "gcCounter function from HMMcopy utilities, used to generate GC content in non-overlapping windows from a fasta", "abricate_run": "Screen assemblies for antimicrobial resistance against multiple databases", "dragonflye": "Assemble bacterial isolate genomes from Nanopore reads"}}, "target": "dragonflye", "target_idx": 4}
{"id": "samplesheet_arch_cfdna_liquid_biopsy_0_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": "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, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "patient,sample,timepoint,volume_ml,fastq_1,fastq_2", "target_idx": 0}
{"id": "schema_std_demultiplex_2_0", "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": {"sample,fastq_1,fastq_2,umi_barcodes": null, "id,samplesheet,lane,flowcell,per_flowcell_manifest": null, "sample,fastq_1": null, "patient,sample,fastq_1,fastq_2,bam": null}}, "target": "id,samplesheet,lane,flowcell,per_flowcell_manifest", "target_idx": 1}
{"id": "mod_crabz_decompress_1", "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": {"shinyngs_app": "build and deploy Shiny apps for interactively mining differential abundance data", "xz_decompress": "Decompresses files with xz.", "sam2lca_analyze": "Calling lowest common ancestors from multi-mapped reads in SAM/BAM/CRAM files", "unzipfiles": "Unzip ZIP archive files", "crabz_decompress": "Decompress files with crabz"}}, "target": "crabz_decompress", "target_idx": 4}
{"id": "noul_modifying_channel_meta_inside_bash_script_block_1", "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": "schema_std_oncoanalyser_2_1", "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_id,group_id,subject_id,sample_type,sequence_type": null, "sample,seq_data,pbi,start_from": null, "sample,nuclear_image,spot_table,membrane_image": null, "sample,trait,pascal,twas,additional_sources": null}}, "target": "sample_id,group_id,subject_id,sample_type,sequence_type", "target_idx": 0}
{"id": "mod_plastid_makewiggle_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create wiggle or bedGraph files from alignment files after applying a read mapping rule (e.g. to map ribosome-protected footprints at their P-sites), for visualization in a genome browser (tools: plastid)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"alignoth": "Creating alignment plots from bam files", "epang_place": "phylogenetic placement of query sequences in a reference tree", "gatk4_filtermutectcalls": "Filters the raw output of mutect2, can optionally use outputs of calculatecontamination and learnreadorientati", "agat_spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "plastid_makewiggle": "Create wiggle or bedGraph files from alignment files after applying a read mapping rule (e.g. to map ribosome-"}}, "target": "plastid_makewiggle", "target_idx": 4}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_6_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 are standard for Paired-end Illumina RNA-seq input samplesheet?", "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_macrel_contigs_1", "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": {"macrel_contigs": "A tool that mines antimicrobial peptides (AMPs) from (meta)genomes by predicting peptides from genomes (provid", "staphscan": "staphscan is a tool to screen genome assemblies of Staphylococcus aureus", "ampcombi2_cluster": "A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete usin", "gatk4_applyvqsr": "Apply a score cutoff to filter variants based on a recalibration table.\nAplyVQSR performs the second pass in a", "ampcombi": "A tool to parse and summarise results from antimicrobial peptides tools and present functional classification."}}, "target": "macrel_contigs", "target_idx": 0}
{"id": "subworkflow_pkg_vcf_impute_minimac4_0", "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": "local_subworkflow_prepontreads_1_3", "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, "Local subworkflow PREPONTREADS": null, "Leave them out": null}}, "target": "Local subworkflow PREPONTREADS", "target_idx": 2}
{"id": "mod_kraken2_kraken2_0", "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": {"scanpy/pca": "Perform principal component analysis (PCA) on single-cell RNA-seq data using Scanpy", "centrifuge/kreport": "Creates Kraken-style reports from centrifuge out files", "conifer": "Calculate confidence scores from Kraken2 output", "shapeit5/ligate": "Ligate multiple phased BCF/VCF files into a single whole chromosome file.\nTypically run to ligate multiple chu", "kraken2/kraken2": "Classifies metagenomic sequence data"}}, "target": "kraken2/kraken2", "target_idx": 4}
{"id": "schema_std_ribomsqc_0_1", "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_id,name,description,path,path_2": null, "id,raw_file": null, "id,fasta,sequence": null, "sample,fastq_1,fastq_2,fasta,run_accession": null}}, "target": "id,raw_file", "target_idx": 1}
{"id": "samplesheet_arch_bulk_rnaseq_pe_4_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": "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": null, "sample,bam": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 3}
{"id": "mod_trycycler_cluster_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Cluster contigs from multiple assemblies by similarity (tools: trycycler)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mash_sketch": null, "cdhit_cdhit": null, "galah": null, "famsa_align": null, "trycycler_cluster": null}}, "target": "trycycler_cluster", "target_idx": 4}
{"id": "mod_somalier_extract_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": {"rpbp_estimatemetagenebayesfactors": null, "atlas_pmd": null, "somalier_extract": null, "hipstr": null, "vcf_extract_relate_somalier": null}}, "target": "somalier_extract", "target_idx": 2}
{"id": "schema_std_hlatyping_0_0", "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,bam,seq_type": null, "condition,type,microbiome_path,alleles,weights_path": null, "sample_id,bam,vcf,library_id,lane": null, "sample,fastq_1,fastq_2,genome": null}}, "target": "sample,fastq_1,fastq_2,bam,seq_type", "target_idx": 0}
{"id": "mod_rseqc_junctionannotation_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": {"leafcutter/clusterregtools": "Cluster RNA-seq junction reads extracted by regtools and refine them based on read counts and ratios for alter", "rseqc/junctionannotation": "compare detected splice junctions to reference gene model", "custom/bed12codonpositions": "Expand a BED12 into a BED6 of in-frame mRNA positions, projected back\nto genomic coordinates. Default behaviou", "utils_nextflow_pipeline": "Subworkflow with functionality that may be useful for any Nextflow pipeline", "humann3/renorm": "Normalizing RPKs to relative abundance"}}, "target": "rseqc/junctionannotation", "target_idx": 1}
{"id": "mod_fastq_qc_trim_filter_setstrandedness_0", "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": {"bowtie2/align": null, "fastq_qc_trim_filter_setstrandedness": null, "adapterremovalfixprefix": null, "bamtofastq10x": null, "s4pred/runmodel": null}}, "target": "fastq_qc_trim_filter_setstrandedness", "target_idx": 1}
{"id": "mod_bam_variant_calling_mpileup_bcftools_1", "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": {"glimpse2_ligate": "Ligatation of multiple phased BCF/VCF files into a single whole chromosome file.\nGLIMPSE2 is run in chunks tha", "bam_variant_calling_mpileup_bcftools": "Subworkflow to compute genotype likelihoods from BAM files using\nbcftools/mpileup and bcftools/call variants b", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "atlas_splitmerge": "split single end read groups by length and merge paired end reads", "stainwarpy_register": "Register H&E stained and Multiplexed tissue images using feature-based image registration"}}, "target": "bam_variant_calling_mpileup_bcftools", "target_idx": 1}
{"id": "mod_sistr_1", "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": {"gemmi_cif2json": "Convert macromolecular structure files from mmCIF format to JSON format using gemmi.", "bedtools_map": "Allows one to screen for overlaps between two sets of genomic features.", "amrfinderplus_run": "Identify antimicrobial resistance in gene or protein sequences", "abricate_run": "Screen assemblies for antimicrobial resistance against multiple databases", "sistr": "Serovar prediction of salmonella assemblies"}}, "target": "sistr", "target_idx": 4}
{"id": "mod_custom_pcaclustering_1", "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": {"whatshap_haplotag": "Tag reads by haplotype", "custom_clustermetrics": "Computes clustering quality metrics (silhouette, Calinski-Harabasz, Davies-Bouldin) and performs k-sweep analy", "picard_scatterintervalsbyns": "Writes an interval list created by splitting a reference at Ns.A Program for breaking up a reference into inte", "bigscape_bigscape": "BiG-SCAPE (Biosynthetic Gene Similarity Clustering and Prospecting Engine) clusters\nbiosynthetic gene clusters", "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_pediatric_trio_somatic_0_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": "Which columns should the input samplesheet have for: Pediatric cancer trio (Child Proband tumor, Proband germline, Parents)?", "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_bam_qc_rnaseq_1", "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": {"bowtie_align": "Align reads to a reference genome using bowtie", "gatk4_unmarkduplicates": "This tool locates and unmark the marked duplicate reads in a BAM or SAM file, where duplicate reads are define", "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", "ctatsplicing_prepgenomelib": "Reference preparation for CTAT-splicing"}}, "target": "bam_qc_rnaseq", "target_idx": 2}
{"id": "samplesheet_arch_rare_disease_trio_6_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 are standard for Trio exome/genome sequencing (Proband, Mother, Father) input samplesheet?", "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": "qc_adapt_ffpe_wes_0_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": "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_blast_tblastn_2", "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_long": null, "process_high": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "noul_channel_join_operator_4", "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_scrna_10x_v3_3_0", "category": "samplesheet_schema", "state": {"assay": "Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry)", "first_step": "FASTQC"}, "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,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_sniffles_1", "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": {"fcsgx_rungx": "Runs FCS-GX (Foreign Contamination Screen - Genome eXtractor) to screen and remove foreign contamination from ", "saltshaker_classify": "mtDNA deletion and duplication classification downstream of mitosalt", "cutesv": "structural-variant calling with cutesv", "force_cube": "Generate processing masks for a give datacube definition and area of interest.\nThese files can be used to spat", "sniffles": "structural-variant calling with sniffles"}}, "target": "sniffles", "target_idx": 4}
{"id": "mod_samtools_splitheader_0", "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": {"samtools/splitheader": "Extract header lines from a SAM/BAM/CRAM file into separate files depending on type", "bcftools/view": "View, subset and filter VCF or BCF files by position and filtering expression. Convert between VCF and BCF", "foldseek/createdb": "Create a database from protein structures", "custom/orfcollapse": "Collapse small ORFs that share an amino-acid sequence cluster into a single\ncatalogue entry. Pair with `custom", "samtools/convert": "convert and then index CRAM -> BAM or BAM -> CRAM file"}}, "target": "samtools/splitheader", "target_idx": 0}
{"id": "noul_channel_mix_operator_21", "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": "qc_adapt_illumina_novaseq_0_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": "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_bbmap_bbnorm_1", "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": {"cellbender_removebackground": "Module to use CellBender to estimate 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", "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", "mitohifi_mitohifi": "A python workflow that assembles mitogenomes from Pacbio HiFi reads"}}, "target": "bbmap_bbnorm", "target_idx": 1}
{"id": "pipe_core10_scrnaseq_2_bare", "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": {"taxprofiler": null, "rnaseq": null, "scrnaseq": null, "atacseq": null, "viralrecon": null, "chipseq": null, "eager": null, "mag": null, "ampliseq": null, "sarek": null}}, "target": "scrnaseq", "target_idx": 2}
{"id": "schema_std_scnanoseq_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/scnanoseq", "assay": "scnanoseq pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/scnanoseq (Single-cell/nuclei pipeline for data derived from Oxford Nan)?", "criteria": {"sample,vcf,tbi": null, "sample,fastq,cell_count": null, "sample,fastq_1,fastq_2,genome": null, "sample,fastq_1,fastq_2,bam,seq_type": null}}, "target": "sample,fastq,cell_count", "target_idx": 1}
{"id": "samplesheet_arch_cancer_somatic_bam_3_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": "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, "patient,sample,bam": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 0}
{"id": "mod_fastqscreen_buildfromindex_1", "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": {"cleanifier_index": "Builds a Cuckoo filter or Cuckoo hash table index from reference sequences (FASTA/FASTQ) for fast contaminatio", "centrifuge_build": "Build centrifuge database for taxonomic profiling", "hisat2_build": "Builds HISAT2 index for reference genome", "fastqscreen_buildfromindex": "Build fastq screen config file from bowtie index files", "myloasm": "Myloasm is a de novo metagenome assembler for long-read sequencing data.\nIt takes sequencing reads and outputs"}}, "target": "fastqscreen_buildfromindex", "target_idx": 3}
{"id": "subworkflow_pkg_fasta_hmmsearch_rank_fastas_3", "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, "Use nf-core subworkflow fasta_hmmsearch_rank_fastas": null, "Leave them out": null, "Local subworkflow FASTA_HMMSEARCH_RANK_FASTAS": null}}, "target": "Use nf-core subworkflow fasta_hmmsearch_rank_fastas", "target_idx": 1}
{"id": "field_constraint_status_0_2", "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, "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_scrna_10x_v3_4_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": "What samplesheet columns are expected when inputs are: Cellular barcode+UMI R1 (28bp) and transcript cDNA R2 (91bp) FASTQs?", "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": "pipe_all101_demultiplex_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for bases2fastq analysis? Specific context: Demultiplexing pipeline for sequencing data. Topics: bases2fastq, bcl2fastq, demultiplexing, elementbiosciences, illumina. ", "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]", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "demultiplex": "Demultiplexing pipeline for sequencing data [bases2fastq, bcl2fastq, demultiplexing]", "sopa": "Nextflow version of Sopa - spatial omics pipeline and analysis [segmentation, spatial-omics, spatial-proteomics]", "molkart": "A pipeline for processing Molecular Cartography data from Resolve Bioscience (combinatorial FISH) [fish, image-processin", "isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a", "riboseq": "Pipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data.", "hlatyping": "Precision HLA typing from next-generation sequencing data [dna, hla, hla-typing]"}}, "target": "demultiplex", "target_idx": 2}
{"id": "pipe_all101_metapep_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for metapep. 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]", "metapep": "From metagenomes to epitopes and beyond", "airrflow": "B-cell and T-cell Adaptive Immune Receptor Repertoire (AIRR) sequencing analysis pipeline using the Immcantation framewo", "hadge": "Comprehensive pipeline for donor demultiplexing in single cell [cell-hashing, deconvolution, demultiplexing]", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina"}}, "target": "metapep", "target_idx": 1}
{"id": "samplesheet_arch_faire_seq_chromatin_4_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": "What samplesheet columns are expected when inputs are: Formaldehyde-assisted isolation of regulatory elements paired-end FASTQs?", "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": "samplesheet_arch_scrna_10x_v3_4_3", "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": "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": null, "sample,fastq_1": 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": "qc_adapt_ont_nanoplot_1_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": "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": "noul_named_process_output_emits_16", "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_ffpe_wes_1_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": "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": "samplesheet_arch_prealigned_cram_indexed_5_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": "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,cram,crai": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null}}, "target": "sample,cram,crai", "target_idx": 1}
{"id": "mod_glimpse2_ligate_0", "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": {"arriba/download": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data.", "vcf_impute_glimpse": "Subworkflow to impute VCF files using GLIMPSE V1 software. The subworkflow\ntakes VCF files, phased reference p", "glimpse/concordance": "Compute the r2 correlation between imputed dosages (in MAF bins) and highly-confident genotype calls from the ", "glimpse2/ligate": "Ligatation of multiple phased BCF/VCF files into a single whole chromosome file.\nGLIMPSE2 is run in chunks tha", "force/tileextent": "Compute valid tiles for a given datacube definition and area of interest.\nThis list can be used by downstream "}}, "target": "glimpse2/ligate", "target_idx": 3}
{"id": "samplesheet_arch_metatranscriptome_denovo_5_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": "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,environment": null, "sample,rrna_fasta": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,environment", "target_idx": 0}
{"id": "qc_adapt_ffpe_wes_2_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": "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": "field_constraint_status_0_11", "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: [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": "mod_ribotish_quality_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": {"paragraph/vcf2paragraph": "Convert a VCF file to a JSON graph", "anota2seq/anota2seqrun": "Generally applicable transcriptome-wide analysis of translational efficiency using anota2seq", "ribotish/quality": "Quality control of riboseq bam data", "agat/spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "dotseq/dotseq": "Detect differential ORF usage (DOU) and ORF-level differential\ntranslation efficiency (DTE) from Ribo-seq with"}}, "target": "ribotish/quality", "target_idx": 2}
{"id": "noul_channel_factory_inside_process_body_9", "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_parabricks_indexgvcf_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: NVIDIA Clara Parabricks GPU-accelerated gvcf indexing tool. (tools: parabricks)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"unzip": "Unzip ZIP archive files", "fqtk": "Demultiplex fastq files", "parabricks_indexgvcf": "NVIDIA Clara Parabricks GPU-accelerated gvcf indexing tool.", "annotsv_annotsv": "Annotation and Ranking of Structural Variation", "aardvark_merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF."}}, "target": "parabricks_indexgvcf", "target_idx": 2}
{"id": "samplesheet_arch_spatial_visium_6_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 are standard for 10x Visium spatial transcriptomics with histology image input samplesheet?", "criteria": {"sample,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": "pipe_all101_metaboigniter_5", "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": {"scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "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 ", "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"}}, "target": "metaboigniter", "target_idx": 2}
{"id": "resource_art_illumina_2", "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_single": null, "process_long": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "pipe_all101_rnaseq_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: 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": {"scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "viralmetagenome": "A nf-core pipeline for untargeted whole genome reconstruction with iSNV detection from metagenomic samples.  [epidemiolo", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "dualrnaseq": "Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous", "stableexpression": "This pipeline is designed to identify the most stable genes in one or more expression datasets (RNA-seq / Microarray). T"}}, "target": "rnaseq", "target_idx": 2}
{"id": "mod_localcdsearch_download_0", "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": {"paragraph/vcf2paragraph": "Convert a VCF file to a JSON graph", "bcftools/csq": "bcftools Haplotype-aware consequence caller", "blast/blastp": "BLASTP (Basic Local Alignment Search Tool- Protein) compares an amino acid (protein) query sequence against a ", "localcdsearch/download": "A command-line tool for downloading databases for local protein domain annotation using NCBI's Conserved Domai", "ucsc/bigwigaverageoverbed": "compute average score of bigwig over bed file"}}, "target": "localcdsearch/download", "target_idx": 3}
{"id": "resource_bcftools_view_5", "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_medium": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "pipe_all101_rnastructurome_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: 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": "a bioinformatics pipeline for analysing chemical high-throughput RNA structure-probing data [dms, map, rna-structure]", "smrnaseq": "A small-RNA sequencing analysis pipeline [small-rna, smrna-seq]", "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", "proteogenomicsdb": "The ProteoGenomics database generation workflow creates different protein databases for ProteoGenomics data analysis. [c", "epitopeprediction": "A bioinformatics best-practice analysis pipeline for epitope prediction and annotation [epitope, epitope-prediction, mhc", "drugresponseeval": "Pipeline for testing drug response prediction models in a statistically and biologically sound way. [cell-lines, cross-v", "bactmap": "A mapping-based pipeline for creating a phylogeny from bacterial whole genome sequences [bacteria, bacterial, bacterial-"}}, "target": "rnastructurome", "target_idx": 0}
{"id": "qc_adapt_pacbio_hifi_0_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": "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_pluginsplit_0", "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_long": null, "process_single": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_autocycler_combine_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge resolved cluster assemblies into final consensus outputs with Autocycler. (tools: autocycler)?", "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.", "ribocode_gtfupdate": "Update GTF annotation file for RiboCode compatibility", "kma_index": "This module wraps the index module of the KMA alignment tool.", "autocycler_resolve": "Resolve trimmed assembly graphs into final contigs within Autocycler.", "fasta_consensus_autocycler": "Generate consensus assemblies and assembly graphs from grouped contig FASTA files using autocycler"}}, "target": "autocycler_combine", "target_idx": 0}
{"id": "mod_biobambam_bammarkduplicates2_0", "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": {"biobambam/bamsormadup": null, "biobambam/bammarkduplicates2": null, "pairtools/select": null, "gatk4spark/markduplicates": null, "primerprospector/analyzeprimers": null}}, "target": "biobambam/bammarkduplicates2", "target_idx": 1}
{"id": "samplesheet_arch_pacbio_hifi_wgs_7_5", "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 PacBio HiFi input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "mod_gatk4_filterintervals_1", "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": {"agat_spextractsequences": null, "gatk4_asereadcounter": null, "vireo": null, "gatk4_filterintervals": null, "gatk4_analyzecovariates": null}}, "target": "gatk4_filterintervals", "target_idx": 3}
{"id": "resource_biscuit_biscuitblaster_4", "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_high": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_cancer_somatic_tn_4_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": "What samplesheet columns are expected when inputs are: Paired-end FASTQs for patient tumor and germline normal tissue?", "criteria": {"sample,fastq_1": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "patient,sample,status,bam,bai": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 1}
{"id": "samplesheet_arch_spatial_visium_5_3", "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": "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,image": null, "sample,bam": null, "sample,fastq_1,image": null}}, "target": "sample,fastq_1,fastq_2,image,slide,area", "target_idx": 0}
{"id": "intent_build_pipeline_5", "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, "prepare_data": null, "ask_question": null, "debug_error": null}}, "target": "build_pipeline", "target_idx": 0}
{"id": "samplesheet_arch_methylseq_bisulfite_2_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 should the input samplesheet have?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,cpg,methylation": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "samplesheet_arch_chipseq_with_control_3_0", "category": "samplesheet_schema", "state": {"assay": "ChIP-seq with IP and input control design", "first_step": "FASTQC"}, "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,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1,fastq_2,antibody,control": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 3}
{"id": "pipe_all101_molkart_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: 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": {"callingcards": null, "rnadnavar": null, "hic": null, "molkart": null, "ribomsqc": null, "pixelator": null, "sopa": null, "rnavar": null}}, "target": "molkart", "target_idx": 3}
{"id": "samplesheet_arch_spatial_visium_1_3", "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 samplesheet have for 10x Visium spatial transcriptomics with histology image?", "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": "qc_adapt_singlecell_multiqc_0_23", "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_spatial_xenium_5_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": "In Nextflow pipeline nf-core/spatialaxe, determine the input samplesheet column structure for: 10x Xenium in situ subcellular spatial RNA transcriptomics.", "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": "samplesheet_arch_atacseq_replicates_6_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 are standard for ATAC-seq chromatin accessibility with biological replicates input samplesheet?", "criteria": {"sample,fastq_1,fastq_2,replicate": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 0}
{"id": "noul_exit_code_137_cause_6", "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": "intent_prepare_data_23", "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": "field_constraint_strandedness_2_10", "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, "type: boolean": null, "pattern: ^[0-9]+$": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 1}
{"id": "mod_cutadapt_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Removes adapter sequences from sequencing reads (tools: cutadapt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/annotateintervals": "Annotates intervals with GC content, mappability, and segmental-duplication content", "chelae/trim": "Adapter and quality trimming of short-read FASTQ data using chelae.", "nail/search": "nail search is a fast and scalable tool for searching protein sequences against protein databases", "hifiadapterfilt/downloaddb": "Downloads the pre-built PacBio adapter BLAST database from the HiFiAdapterFilt\nGitHub repository. The database", "cutadapt": "Removes adapter sequences from sequencing reads"}}, "target": "cutadapt", "target_idx": 4}
{"id": "qc_adapt_qc_aggregate_2_19", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample QC aggregation and reporting (multiqc_report).", "criteria": {"Swap for NanoPlot": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "field_constraint_fastq_2_2_10", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'fastq_2' (Path to read 2 FASTQ file for paired-end sequencing) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'fastq_2' validated?", "criteria": {"pattern: ^\\S+\\.bam$": null, "enum: [0, 1]": null, "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": "samplesheet_arch_rnafusion_pe_6_2", "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 are standard for RNA gene fusion detection (Arriba, STAR-Fusion) input samplesheet?", "criteria": {"sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,fastq_2": null, "sample,fusion_bed": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 0}
{"id": "noul_workflow_completion_lifecycle_hook_9", "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": "samplesheet_arch_metatranscriptome_denovo_0_5", "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 should the input samplesheet have for: Environmental community metatranscriptomics de novo assembly?", "criteria": {"sample,bam": 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": "intent_prepare_data_15", "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, "build_pipeline": null, "ask_question": null, "debug_error": null}}, "target": "prepare_data", "target_idx": 0}
{"id": "qc_adapt_ffpe_wes_2_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": "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_bulk_multiqc_1_12", "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": "pipe_all101_scrnaseq_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": {"cutandrun": "Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak callin", "drugresponseeval": "Pipeline for testing drug response prediction models in a statistically and biologically sound way. [cell-lines, cross-v", "reportho": "nf-core pipeline for comparative analysis of ortholog predictions [ortholog]", "riboseq": "Pipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data.", "dualrnaseq": "Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous", "slamseq": "SLAMSeq processing and analysis pipeline [differential-expression, quantseq, slamseq]", "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", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "fastqrepair": "A pipeline that can be used to recover corrupted FASTQ.gz files, drop or fix uncompliant reads, remove unpaired reads, a"}}, "target": "scrnaseq", "target_idx": 8}
{"id": "mod_survivor_stats_1", "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": {"survivor_stats": "Report multiple stats over a VCF file", "finaletoolkit_endmotifs": "Measure the frequency of 5' k-mer end motifs.", "sparsesignatures": "mutational signature deconvolution of cancer cells", "survivor_filter": "Filter a vcf file based on size and/or regions to ignore", "agat_sqstatbasic": "Provides basic statistics in text format from a GFF/GTF annotation file"}}, "target": "survivor_stats", "target_idx": 0}
{"id": "subworkflow_pkg_bam_subsampledepth_samtools_1", "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": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow bam_subsampledepth_samtools": null, "Local subworkflow BAM_SUBSAMPLEDEPTH_SAMTOOLS": null, "Leave them out": null}}, "target": "Use nf-core subworkflow bam_subsampledepth_samtools", "target_idx": 1}
{"id": "mod_msisensor_scan_0", "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": null, "msisensor/msi": null, "salsa2": null, "msisensor2/msi": null, "vclust/align": null}}, "target": "msisensor/scan", "target_idx": 0}
{"id": "samplesheet_arch_bulk_wes_pe_6_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 are standard for Paired-end Whole Exome Sequencing (WES) target capture input samplesheet?", "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": "noul_confusing_combine_with_mix_semantics_1", "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_bamcmp_3", "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_long": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "field_constraint_fastq_2_0_7", "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": "samplesheet_arch_viral_amplicon_artic_0_2", "category": "samplesheet_schema", "state": {"assay": "Viral amplicon sequencing with primers", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have 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_bedtools_unionbedg_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Combines multiple BedGraph files into a single file (tools: bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"salmon_index": "Create index for salmon", "agat_convertbed2gff": "Takes a bed12 file and converts to a GFF3 file", "bamtools_convert": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "shinyngs_staticexploratory": "Make exploratory plots for analysis of matrix data, including PCA, Boxplots and density plots", "bedtools_unionbedg": "Combines multiple BedGraph files into a single file"}}, "target": "bedtools_unionbedg", "target_idx": 4}
{"id": "resource_antismash_antismashlite_0", "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_long": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "pipe_all101_fastquorum_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: 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": {"oncoanalyser": null, "proteinfold": null, "drugresponseeval": null, "smrnaseq": null, "fastquorum": null, "proteogenomicsdb": null, "bacass": null, "viralmetagenome": null, "stableexpression": null, "seqinspector": null}}, "target": "fastquorum", "target_idx": 4}
{"id": "noul_executor_support_24", "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_metagenome_mag_grouped_1_4", "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 Metagenomic MAG assembly with comparative groups?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null, "sample,bam": null, "sample,fasta": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 1}
{"id": "mod_quantify_rsem_0", "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": {"dotseq/dotseq": "Detect differential ORF usage (DOU) and ORF-level differential\ntranslation efficiency (DTE) from Ribo-seq with", "quantify_rsem": "Perform quantification with RSEM to produce count tables, legacy merge matrices, and SummarizedExperiment obje", "ctatsplicing/prepgenomelib": "Reference preparation for CTAT-splicing", "strdust": "Tandem repeat genotyper for long reads", "samtools/flagstat": "Counts the number of alignments in a BAM/CRAM/SAM file for each FLAG type"}}, "target": "quantify_rsem", "target_idx": 1}
{"id": "mod_multiseqdemux_0", "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": {"bam_impute_stitch": null, "gatk4/concordance": null, "multiseqdemux": null, "bff": null, "popscle/demuxlet": null}}, "target": "multiseqdemux", "target_idx": 2}
{"id": "mod_rastair_mbias_1", "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_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", "tetranscripts": "Runs TEtranscripts which summarises transposable element content of a bam file.", "rastair_mbias": "Assess C->T conversion as a readout for methylation on a per-read-position basis.", "metator_pipeline": "Metagenomic Tridimensional Organisation-based Reassembly - A set of scripts that streamlines the processing an"}}, "target": "rastair_mbias", "target_idx": 3}
{"id": "mod_metaphlan3_metaphlan3_1", "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": {"bracken_combinebrackenoutputs": "Combine output of metagenomic samples analyzed by bracken.", "tidk_search": "Searches a genome for a telomere string such as TTAGGG", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "muse_sump": "Computes tier-based cutoffs from a sample-specific error model which is generated by muse/call and reports the", "metaphlan3_metaphlan3": "MetaPhlAn is a tool for profiling the composition of microbial communities from metagenomic shotgun sequencing"}}, "target": "metaphlan3_metaphlan3", "target_idx": 4}
{"id": "noul_single_hyphen_cli_params_error_17", "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_arriba_arriba_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", "legsta": "Typing of clinical and environmental isolates of Legionella pneumophila", "circexplorer2/parse": "CIRCexplorer2 parses fusion junction files from multiple aligners to prepare them for CIRCexplorer2 annotate.", "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_pe_illumina_fastqc_2_47", "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_pe_illumina_fastqc_1_39", "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_spatial_visium_7_1", "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 grouped metagenomics?", "criteria": {"sample,image": null, "sample,fastq_1,fastq_2,image,slide,area": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,image,slide,area", "target_idx": 1}
{"id": "mod_fasta_clean_fcs_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Foreign Contamination Screen (FCS) is a tool suite for identifying and removing contaminant sequences in genome assemblies (tools: fasta_clean_fcs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fcsgx/cleangenome": "Runs FCS-GX (Foreign Contamination Screen - Genome eXtractor) to remove foreign contamination from genome asse", "fasta_clean_fcs": "Foreign Contamination Screen (FCS) is a tool suite for identifying and removing contaminant sequences in genom", "pbmarkdup": "Takes one or multiple sequencing chips of an amplified library as HiFi reads and marks or removes\nduplicates.", "amrfinderplus/run": "Identify antimicrobial resistance in gene or protein sequences", "genotyphi/parse": "Genotype Salmonella Typhi from Mykrobe results"}}, "target": "fasta_clean_fcs", "target_idx": 1}
{"id": "mod_mindagap_duplicatefinder_0", "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": {"imc2mc": "Staging module transforming Imaging Mass Cytometry .txt files to .tif files with OME-XML metadata. Includes op", "helitronscanner/scan": "HelitronScanner scanHead and scanTail tools for Helitron transposons in genomes", "mindagap/duplicatefinder": "marks duplicate spots along gridline edges.", "rbt/vcfsplit": "A tool for splitting VCF/BCF files into N equal chunks, including BND support", "bftools/showinf": "Extract OME xml data from OME-tif"}}, "target": "mindagap/duplicatefinder", "target_idx": 2}
{"id": "samplesheet_arch_bulk_wgs_pe_0_2", "category": "samplesheet_schema", "state": {"assay": "Standard Paired-end Whole Genome Sequencing (WGS)", "first_step": "FASTQC"}, "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": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "resource_antismash_antismash_3", "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_high": null, "process_medium": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "noul_named_output_channel_access_17", "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": "qc_adapt_qc_aggregate_2_30", "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": "resource_bcftools_rohviz_3", "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_long": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_bcftools_plugintag2tag_1", "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": {"bcftools_index": null, "duckdb_table2parquet": null, "pairtools_restrict": null, "bcftools_call": null, "bcftools_plugintag2tag": null}}, "target": "bcftools_plugintag2tag", "target_idx": 4}
{"id": "schema_std_nanostring_2_1", "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,fastq_1": null, "SAMPLE_ID,RCC_FILE,RCC_FILE_NAME,TIME,TREATMENT": null, "sample,fastq_1,fastq_2,batch,condition": null, "sample,id,data_path,fastq_dir,cytaimage": null}}, "target": "SAMPLE_ID,RCC_FILE,RCC_FILE_NAME,TIME,TREATMENT", "target_idx": 1}
{"id": "resource_bamutil_trimbam_2", "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_long": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_sageproteomics_sage_0", "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": {"comet": "Comet is an open source tandem mass spectrometry (MS/MS) sequence database search tool", "diamond/cluster": "calculate clusters of highly similar sequences", "soupx": "Estimation and removal of cell free mRNA contamination in droplet based single cell RNA-seq data.\n\nThe filtere", "regenie/runl1": "Finish REGENIE step 1 from split level-0 prediction files", "sageproteomics/sage": "sage is a search software for proteomics data"}}, "target": "sageproteomics/sage", "target_idx": 4}
{"id": "resource_agat_spflagshortintrons_1", "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_long": null, "process_high": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_bam_cnv_wisecondorx_1", "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": {"transrate": null, "bam_cnv_wisecondorx": null, "canvas_germline": null, "rrnatranscripts": null, "cnvnator_convert2vcf": null}}, "target": "bam_cnv_wisecondorx", "target_idx": 1}
{"id": "mod_qcatch_1", "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": {"sawfish_jointcall": "Joint calling of structural variants from multiple samples using Sawfish", "quantmsutils_mzmlstatistics": "Generate statistics from mzML files using quantms-utils", "anndata_barcodes": "Module to subset AnnData object to cells with matching barcodes from the csv file", "qcatch": "Cell-filtering and QC reporting tool for alevin-fry quantification results", "arcane_filter": "Filter GTF annotations and genome sequence for alignment-free single-cell RNA-seq quantification with Arcane"}}, "target": "qcatch", "target_idx": 3}
{"id": "field_constraint_bam_1_12", "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": "noul_channel_factory_inside_process_body_16", "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_ffpe_wes_1_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": "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": "core_tool_fastp_bare_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": {"fastqc": null, "multiqc": null, "trimmomatic": null, "cutadapt": null, "fastp": null}}, "target": "fastp", "target_idx": 4}
{"id": "mod_bcftools_mpileup_0", "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": {"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.", "pbmarkdup": "Takes one or multiple sequencing chips of an amplified library as HiFi reads and marks or removes\nduplicates.", "hamronization/abricate": "Tool to convert and summarize ABRicate outputs using the hAMRonization specification", "bcftools/mpileup": "Compresses VCF files"}}, "target": "bcftools/mpileup", "target_idx": 4}
{"id": "samplesheet_arch_bulk_rnaseq_pe_0_5", "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 for: Paired-end Illumina RNA-seq with strandedness?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 2}
{"id": "noul_channel_collect_operator_4", "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_baysor_run_1", "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_long": null, "process_low": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_fgumi_zipper_0", "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/zipper": "Zip an unmapped UMI BAM together with its aligned BAM using fgumi", "tcoffee/seqreformat": "Reformats files with t-coffee", "gatk4/unmarkduplicates": "This tool locates and unmark the marked duplicate reads in a BAM or SAM file, where duplicate reads are define", "fgumi/dedup": "Mark or remove PCR duplicates using UMI information with fgumi", "fgbio/collectduplexseqmetrics": "Collects a suite of metrics to QC duplex sequencing data."}}, "target": "fgumi/zipper", "target_idx": 0}
{"id": "resource_atlas_splitmerge_3", "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_low": null, "process_single": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_ont_metagenome_single_1_5", "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 samplesheet have for Long-read Oxford Nanopore environmental metagenomic sequencing?", "criteria": {"sample,fastq_1": 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": "subworkflow_pkg_faa_seqfu_seqkit_3", "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": {"Use nf-core subworkflow faa_seqfu_seqkit": null, "Local 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": 0}
{"id": "mod_severus_1", "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": {"bam_tumor_normal_somatic_variant_calling_gatk": null, "rtgtools_svdecompose": null, "severus": null, "merquryfk_katgc": null, "delly_call": null}}, "target": "severus", "target_idx": 2}
{"id": "mod_finaletoolkit_wps_1", "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.", "agat_spfilterfeaturefromkilllist": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID", "bam_qc_picard": "Produces comprehensive statistics from BAM file", "finaletoolkit_wps": "Calculate the windowed protection score (WPS; Snyder et al., 2016)\nfrom a BAM file and a list of transcription", "cooler_zoomify": "Generate a multi-resolution cooler file by coarsening"}}, "target": "finaletoolkit_wps", "target_idx": 3}
{"id": "resource_biscuit_qc_1", "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_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_elprep_merge_1", "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": {"ascat": null, "holodeck_mutate": null, "bamaligncleaner": null, "rhocall_viz": null, "elprep_merge": null}}, "target": "elprep_merge", "target_idx": 4}
{"id": "intent_prepare_data_3", "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_tcoffee_tcs_1", "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": {"thermorawfileparser": null, "alignoth": null, "staphopiasccmec": null, "tcoffee_tcs": null, "abra2": null}}, "target": "tcoffee_tcs", "target_idx": 3}
{"id": "pipe_all101_ribomsqc_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: 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": {"stableexpression": "This pipeline is designed to identify the most stable genes in one or more expression datasets (RNA-seq / Microarray). T", "bactmap": "A mapping-based pipeline for creating a phylogeny from bacterial whole genome sequences [bacteria, bacterial, bacterial-", "ribomsqc": "QC pipeline that monitors mass spectrometer performance in ribonucleoside analysis", "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"}}, "target": "ribomsqc", "target_idx": 2}
{"id": "mod_cooler_cload_1", "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": {"cooler_cload": null, "imc2mc": null, "cooltools_insulation": null, "cooler_zoomify": null, "seqkit_replace": null}}, "target": "cooler_cload", "target_idx": 0}
{"id": "schema_std_radseq_0_1", "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,group,path,ref,method": null, "sample,fastq_1,strandedness": null, "sample,fastq_1,fastq_2,rundir,tags": null, "sample,fastq_1,fastq_2,umi_barcodes": null}}, "target": "sample,fastq_1,fastq_2,umi_barcodes", "target_idx": 3}
{"id": "mod_dragonflye_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Assemble bacterial isolate genomes from Nanopore reads (tools: dragonflye)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"shovill": null, "dragonflye": null, "sgdemux": null, "abricate/summary": null, "aria2": null}}, "target": "dragonflye", "target_idx": 1}
{"id": "resource_anota2seq_anota2seqrun_1", "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_long": null, "process_medium": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_sambamba_markdup_0", "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": "find and mark duplicate reads in BAM file", "telomerehunter": "In silico estimation of telomere content and composition from cancer genomes", "picard/fixmateinformation": "Verify mate-pair information between mates and fix if needed", "gatk4/markduplicates": "This tool locates and tags duplicate reads in a BAM or SAM file, where duplicate reads are defined as originat", "biobambam/bamsormadup": "Parallel sorting and duplicate marking"}}, "target": "sambamba/markdup", "target_idx": 0}
{"id": "schema_std_scrnaseq_0_0", "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": {"sample,condition,assay,peak_file,footprinting": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,fastq_barcode,expected_cells": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,fastq_barcode,expected_cells", "target_idx": 2}
{"id": "mod_vardictjava_1", "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": {"viennarna_rnalfold": "calculate locally stable secondary structures of RNAs", "atlas_call": "generate VCF file from a BAM file using various calling methods", "trycycler_cluster": "Cluster contigs from multiple assemblies by similarity", "bcftools_consensus": "Compresses VCF files", "vardictjava": "The Java port of the VarDict variant caller"}}, "target": "vardictjava", "target_idx": 4}
{"id": "mod_coptr_merge_1", "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": null, "circularmapper_circulargenerator": null, "metaphlan_makedb": null, "rnaquast": null, "coptr_estimate": null}}, "target": "coptr_merge", "target_idx": 0}
{"id": "qc_adapt_singlecell_multiqc_1_40", "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": "qc_adapt_pe_illumina_fastqc_2_28", "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": "resource_braker3_0", "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_single": null, "process_low": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_agat_spmergeannotations_5", "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_low": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "field_constraint_bai_0_3", "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_sawfish_discover_1", "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_jointcall": "Joint calling of structural variants from multiple samples using Sawfish", "sawfish_discover": "SV candidate discovery from PacBio HiFi data", "saltshaker_plot": "mtDNA deletion and duplication plotting downstream of mitosalt", "hlala_typing": "Performs HLA typing based on a population reference graph and employs a new linear projection method to align ", "jvarkit_vcffilterjdk": "Filtering VCF with dynamically-compiled java expressions"}}, "target": "sawfish_discover", "target_idx": 1}
{"id": "samplesheet_arch_viral_amplicon_artic_3_0", "category": "samplesheet_schema", "state": {"assay": "Viral amplicon sequencing with primers", "first_step": "FASTQC"}, "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,fastq_1,fastq_2": null, "sample,fasta": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "schema_std_genomeassembler_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/genomeassembler", "assay": "genomeassembler pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/genomeassembler (Assembly and scaffolding of haploid / unphased genomes from )?", "criteria": {"sample,run,group,short_reads_1,short_reads_2": null, "sample,group,ref_fasta,ref_gff,use_ref": null, "sample,id,data_path,fastq_dir,cytaimage": null, "sample,fastq_1,fastq_2,library_id,lane": null}}, "target": "sample,group,ref_fasta,ref_gff,use_ref", "target_idx": 1}
{"id": "resource_backsub_1", "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_long": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "field_constraint_sex_1_6", "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, "pattern: ^\\S+\\.gz$": null, "type: boolean": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 0}
{"id": "mod_nanoplot_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run NanoPlot on nanopore-sequenced reads (tools: nanoplot)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"umicollapse": "Deduplicate reads based on the mapping co-ordinate and the UMI attached to the read.", "msisensorpro/baseline": "MSIsensor-pro/baseline builds a baseline microsatellite file from a panel of normal samples, for use with msis", "biscuit/qc": "Perform basic quality control on a BAM file generated with Biscuit", "chelae/trim": "Adapter and quality trimming of short-read FASTQ data using chelae.", "nanoplot": "Run NanoPlot on nanopore-sequenced reads"}}, "target": "nanoplot", "target_idx": 4}
{"id": "core_tool_gatk_haplotypecaller_described_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": {"gatk_haplotypecaller": "Call germline SNPs and indels via local de-novo assembly of haplotypes", "freebayes": "Bayesian genetic variant detector", "mutect2": "Somatic variant caller", "strelka2": "Fast variant caller", "deepvariant": "Deep learning-based variant caller"}}, "target": "gatk_haplotypecaller", "target_idx": 0}
{"id": "samplesheet_arch_scrna_10x_v3_6_1", "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 are standard for Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry) input samplesheet?", "criteria": {"sample,matrix,barcodes,features": 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": "subworkflow_pkg_opt_flip_track_stat_2", "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": {"Use nf-core subworkflow opt_flip_track_stat": null, "Local subworkflow OPT_FLIP_TRACK_STAT": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Use nf-core subworkflow opt_flip_track_stat", "target_idx": 0}
{"id": "mod_metabat2_metabat2_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Metagenome binning of contigs (tools: metabat2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"clame": "binning of metagenomic sequences", "metabat2_metabat2": "Metagenome binning of contigs", "csvtk_sort": "Sort  CSV (or TSV) tables", "ngsbits_samplegender": "Determines the gender of a sample from the BAM/CRAM file.", "ngsbits_bedcoverage": "Annotates a BED file with the average coverage of the regions from one or several BAM/CRAM file(s)."}}, "target": "metabat2_metabat2", "target_idx": 1}
{"id": "resource_agat_convertspgff2tsv_0", "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_low": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_arriba_visualisation_0", "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_high": null, "process_low": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "noul_workflow_completion_lifecycle_hook_24", "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_biscuit_align_0", "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_long": null, "process_high": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "resource_beagle5_beagle_4", "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_single": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_kma_index_0", "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": {"seqtk/subseq": null, "alignoth": null, "busco/phylogenomics": null, "kma/index": null, "deeptools/bamcoverage": null}}, "target": "kma/index", "target_idx": 3}
{"id": "mod_fairy_sketch_0", "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": {"ska/fasta": "Create genome sketch using split k-mers", "fairy/sketch": "Sketches FASTQ reads into binary sketch (.bcsp) files for alignment-free coverage estimation.", "mmseqs_contig_taxonomy": "Assign taxonomy to contigs using the MMseqs2 workflow.", "gatk4spark/applybqsr": "Apply base quality score recalibration (BQSR) to a bam file", "skani/triangle": "All-to-all ANI computation."}}, "target": "fairy/sketch", "target_idx": 1}
{"id": "mod_bracken_bracken_0", "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": {"pbtk/bam2fastq": "converts pacbio bam files to fastq.gz using PacBioToolKit (pbtk) bam2fastq", "argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD).", "bracken/build": "Extends a Kraken2 database to be compatible with Bracken", "bracken/bracken": "Re-estimate taxonomic abundance of metagenomic samples analyzed by kraken.", "osfclient/fetch": "A python library and a command-line client for up- and downloading files to and from your Open Science Framewo"}}, "target": "bracken/bracken", "target_idx": 3}
{"id": "mod_bamclipper_0", "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": {"leehom": null, "annotsv/annotsv": null, "bamclipper": null, "bedtools/shuffle": null, "gatk4/cleansam": null}}, "target": "bamclipper", "target_idx": 2}
{"id": "noul_invalid_process_communication_via_globals_22", "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_integronfinder_1", "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": {"integronfinder": null, "bcftools_isec": null, "antismash_antismash": null, "pharokka_pharokka": null, "amrfinderplus_update": null}}, "target": "integronfinder", "target_idx": 0}
{"id": "mod_kallistobustools_count_0", "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": {"kallistobustools/count": null, "cellbender/merge": null, "universc": null, "gem2/gem2bedmappability": null, "gedi/indexgenome": null}}, "target": "kallistobustools/count", "target_idx": 0}
{"id": "mod_dragmap_align_1", "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": {"ashlar": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration", "dragmap_align": "Performs fastq alignment to a reference using DRAGMAP", "humid": "HUMID is a tool to quickly and easily remove duplicate reads from FASTQ files, with or without UMIs.", "sylph_query": "Sylph query command for querying genome databases against reads/metagenomes", "alignoth": "Creating alignment plots from bam files"}}, "target": "dragmap_align", "target_idx": 1}
{"id": "mod_fastq_align_bwa_0", "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": null, "ampcombi2/cluster": null, "gt/stat": null, "ampcombi2/parsetables": null, "chelae/trim": null}}, "target": "fastq_align_bwa", "target_idx": 0}
{"id": "resource_bclconvert_2", "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_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "noul_channel_filter_operator_7", "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_bcftools_call_1", "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": {"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", "quantify_rsem": "Perform quantification with RSEM to produce count tables, legacy merge matrices, and SummarizedExperiment obje", "mcstaging_phenoimager2mc": "Staging module for MCMICRO transforming PhenoImager .tif files into stacked and normalized ome-tif files per c", "bcftools_call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily"}}, "target": "bcftools_call", "target_idx": 4}
{"id": "mod_cellrangeratac_mkfastq_0", "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": {"gridss/assemble": "Assemble breakend contigs for GRIDSS structural variant calling", "cellrangeratac/mkfastq": "Module to create fastqs needed by the 10x Genomics Cell Ranger ATAC tool. Uses the cellranger-atac mkfastq com", "bbmap/align": "Align short or PacBio reads to a reference genome using BBMap", "dragonflye": "Assemble bacterial isolate genomes from Nanopore reads", "bowtie/build": "Create bowtie index for reference genome"}}, "target": "cellrangeratac/mkfastq", "target_idx": 1}
{"id": "mod_folddisco_query_1", "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": {"folddisco_query": "Search a prebuilt folddisco index for a discontinuous residue motif in a query protein structure", "mash_dist": "Calculate Mash distances between reference and query sequences", "bbmap_sendsketch": "Compares query sketches to reference sketches hosted on a remote server via the Internet.", "sentieon_rsemcalculateexpression": "Calculate expression with RSEM", "ragtag_patch": "Homology-based assembly patching: Make continuous joins and fill gaps in 'target.fa' using sequences from 'que"}}, "target": "folddisco_query", "target_idx": 0}
{"id": "qc_adapt_bulk_multiqc_0_13", "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": "subworkflow_pkg_archive_extract_0", "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, "Keep the modules in the main workflow": null, "Use nf-core subworkflow archive_extract": null}}, "target": "Use nf-core subworkflow archive_extract", "target_idx": 3}
{"id": "samplesheet_arch_singlecell_parse_splitseq_4_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": "What samplesheet columns are expected when inputs are: Combinatorial split-pool barcoded FASTQs with subpool annotations?", "criteria": {"sample,well,plate": 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": "resource_abricate_summary_4", "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_high": null, "process_low": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "resource_bowtie_align_1", "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_medium": null, "process_high": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_abricate_run_1", "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_low": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_fasttree_0", "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": {"epang/place": null, "epang/split": null, "fasttree": null, "wittyer": null, "cooler/dump": null}}, "target": "fasttree", "target_idx": 2}
{"id": "samplesheet_arch_pacbio_hifi_wgs_6_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 are standard for Long-read Pacific Biosciences HiFi sequencing input samplesheet?", "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": "resource_agat_sqstatbasic_2", "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_high": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "schema_std_variantbenchmarking_1_1", "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,fasta,protein,gbk,gff": null, "id,samplesheet,lane,flowcell,per_flowcell_manifest": null, "fastq_1,fastq_2,batch,amp_batches,seq_batches": null, "id,test_vcf,test_regions,caller,subsample": null}}, "target": "id,test_vcf,test_regions,caller,subsample", "target_idx": 3}
{"id": "mod_beagle5_beagle_1", "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": {"eagle2": null, "purecn_run": null, "beagle5_beagle": null, "glimpse2_phase": null, "cnvkit_genemetrics": null}}, "target": "beagle5_beagle", "target_idx": 2}
{"id": "mod_cat_cat_0", "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": {"oarfish/alignmentmode": "oarfish is a program for quantifying transcript-level expression from long-read sequencing technologies. Quant", "stadeniolib/scramble": "Advanced sequence file format conversions", "find/concatenate": "A module for concatenation of gzipped or uncompressed files getting around UNIX terminal argument size", "qsv/cat": "Concatenate two or more CSV (or TSV) tables into a single table", "cat/cat": "A module for concatenation of gzipped or uncompressed files"}}, "target": "cat/cat", "target_idx": 4}
{"id": "field_constraint_expected_cells_0_13", "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, "type: integer, minimum: 100, maximum: 50000": null, "format: file-path": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 2}
{"id": "qc_adapt_illumina_novaseq_2_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": "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": "pipe_all101_sarek_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: 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": {"denovotranscript": "A pipeline for de novo transcriptome assembly of paired-end short reads from bulk RNA-seq [denovo-assembly, rna-seq, tra", "detaxizer": "A pipeline to identify (and remove) certain sequences from raw genomic data. Default taxon to identify (and remove) is H", "slamseq": "SLAMSeq processing and analysis pipeline [differential-expression, quantseq, slamseq]", "kmermaid": " k-mer similarity analysis pipeline [k-mer, kmer, kmer-counting]", "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", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples [amplicon, artic, assembly]", "oncoanalyser": "A comprehensive cancer DNA/RNA analysis and reporting pipeline [cancer, clinical, ctdna]"}}, "target": "sarek", "target_idx": 5}
{"id": "mod_ampcombi2_cluster_1", "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": {"amplify_predict": null, "annotsv_installannotations": null, "amps": null, "jvarkit_dict2bed": null, "ampcombi2_cluster": null}}, "target": "ampcombi2_cluster", "target_idx": 4}
{"id": "noul_undeclared_process_file_inputs_19", "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": "core_tool_kallisto_bustools_described_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": {"kallisto_bustools": "Kallisto bustools workflow for rapid single-cell RNA-seq quantification and UMI counting", "starsolo": "STAR single-cell", "salmon": "Bulk quantifier", "alevin": "Salmon single-cell", "cellranger": "10x Chromium pipeline"}}, "target": "kallisto_bustools", "target_idx": 0}
{"id": "mod_mcroni_0", "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": {"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.", "autocycler/compress": "Package candidate assemblies for clustering by Autocycler.", "ngsbits/samplegender": "Determines the gender of a sample from the BAM/CRAM file.", "mcroni": "Analysis of mcr-1 gene (mobilized colistin resistance) for sequence variation"}}, "target": "mcroni", "target_idx": 4}
{"id": "noul_modular_subworkflow_composition_17", "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_sylph_sketchsamples_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": {"fairy/sketch": "Sketches FASTQ reads into binary sketch (.bcsp) files for alignment-free coverage estimation.", "skani/dist": "Simple ANI calculation between reference and query genomes.", "sylph/sketchsamples": "Sketching/indexing sequencing reads", "ensemblvep/vep": "Ensembl Variant Effect Predictor (VEP). The output-file-format is controlled through `task.ext.args`.", "samtools/merge": "Merge BAM or CRAM file"}}, "target": "sylph/sketchsamples", "target_idx": 2}
{"id": "qc_adapt_targeted_amplicon_2_8", "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": "samplesheet_arch_chipseq_with_control_4_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": "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": null, "sample,fastq_1,fastq_2,antibody,control": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 3}
{"id": "pipe_all101_riboseq_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for riboseq analysis? Specific context: Pipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data.. ", "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", "proteinannotator": "Generation of sequence-level annotations for amino acid sequences [annotation, proteomics]", "longraredisease": "Long read sequencing pipeline to identify variants in patients with neurodevelopmental disorders  [nanopore, pacbio]", "seqinspector": "Dedicated QC-only pipeline for sequencing data. The pipeline will run a (potentially large) set of QC tools and can outp", "hlatyping": "Precision HLA typing from next-generation sequencing data [dna, hla, hla-typing]", "rangeland": "Pipeline for remotely sensed imagery. The pipeline processes satellite imagery alongside auxiliary data in multiple step", "pacvar": "Longread PacBio sequencing processing for WGS and PureTarget [alignment, long-read, pacbio]", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples [amplicon, artic, assembly]", "riboseq": "Pipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data.", "magmap": "Best-practice analysis pipeline for mapping reads to a (large) collections of genomes"}}, "target": "riboseq", "target_idx": 8}
{"id": "mod_bwa_samse_0", "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", "bwamem2/mem": "Performs fastq alignment to a fasta reference using BWA", "bwa/aln": "Find SA coordinates of the input reads for bwa short-read mapping", "fastq_align_hisat2": "Align reads to a reference genome using hisat2 then sort with samtools", "fastqscan": "FASTQ summary statistics in JSON format"}}, "target": "bwa/samse", "target_idx": 0}
{"id": "mod_bamtools_convert_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.", "atlas/pmd": "Estimate the post-mortem damage patterns of DNA", "repeatmasker/rmouttogff3": "A utility script to assist to convert old RepeatMasker *.out files to version 3 gff files.", "merqury/merqury": "k-mer based assembly evaluation.", "bamtools/convert": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files."}}, "target": "bamtools/convert", "target_idx": 4}
{"id": "mod_cowpy_0", "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": {"cowpy": "Print any text in a cow or other characters", "glimpse2/concordance": "Program to compute the genotyping error rate at the sample or marker level.", "samclip": "Filters SAM/BAM/CRAM files for soft and hard clipped alignments", "clame": "binning of metagenomic sequences", "paragraph/vcf2paragraph": "Convert a VCF file to a JSON graph"}}, "target": "cowpy", "target_idx": 0}
{"id": "mod_gapseq_draft_1", "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": {"popscle_freemuxlet": "Software to deconvolute sample identity and identify multiplets when multiple samples are pooled by barcoded s", "gapseq_requestdb": "Download gapseq reference sequence database for metabolic pathway prediction", "gapseq_doall": "Complete gapseq workflow from genome to gap-filled model", "iphop_predict": "Predict phage host using iPHoP", "gapseq_draft": "Create draft metabolic model from pathway and transporter predictions"}}, "target": "gapseq_draft", "target_idx": 4}
{"id": "noul_exit_code_137_cause_5", "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_bulk_rnaseq_se_2_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 should the input samplesheet have?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,strandedness": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 3}
{"id": "mod_oarfish_readmode_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. 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": {"ariba_getref": "Download and prepare database for Ariba analysis", "biscuit_index": "Indexes a reference genome for use with Biscuit", "ariba_run": "Query input FASTQs against Ariba formatted databases", "oarfish_readmode": "oarfish is a program for quantifying transcript-level expression from long-read sequencing technologies. Map r", "ctree": "Clone trees for Cancer Evolution studies from bulk sequencing data."}}, "target": "oarfish_readmode", "target_idx": 3}
{"id": "qc_adapt_ont_nanoplot_2_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": "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": "resource_antismash_antismash_4", "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_high": null, "process_medium": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_gatk4_unmarkduplicates_1", "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": {"fibertoolsrs_addnucleosomes": null, "gatk4_unmarkduplicates": null, "narfmap_hashtable": null, "abra2": null, "ascat": null}}, "target": "gatk4_unmarkduplicates", "target_idx": 1}
{"id": "mod_cleanifier_filter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Fast, lightweight contamination removal from microbiome data (FASTQ) using a probabilistic Cuckoo filter or Cuckoo hash table index (tools: cleanifier)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"strdrop/build": "Build reference json from sequencing coverage in STR VCFs", "argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD).", "mdust": "mdust from DFCI Gene Indices Software Tools for masking low-complexity DNA sequences", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "cleanifier/filter": "Fast, lightweight contamination removal from microbiome data (FASTQ) using a probabilistic Cuckoo filter or Cu"}}, "target": "cleanifier/filter", "target_idx": 4}
{"id": "mod_kled_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: An ultra-fast and sensitive structural variant detection tool for long-read sequencing data. (tools: kled)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mirdeep2_mirdeep2": null, "last_postmask": null, "agat_spflagshortintrons": null, "alignoth": null, "kled": null}}, "target": "kled", "target_idx": 4}
{"id": "resource_bwa_index_1", "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_medium": null, "process_single": null, "process_high": null}}, "target": "process_high", "target_idx": 3}
{"id": "qc_adapt_bulk_multiqc_0_44", "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_busco_download_0", "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": {"cnaqc": "Quality control of copy number data from bulk WGS assays", "biscuit/qc": "Perform basic quality control on a BAM file generated with Biscuit", "viralconsensus": "Fast and memory-efficient viral consensus genome sequence generation from read alignments", "busco/download": "Download database for BUSCO", "fastq_find_mirna_mirdeep2": "This subworkflow identifies miRNAs from FASTQ files using miRDeep2. The workflow converts FASTQ to FASTA, proc"}}, "target": "busco/download", "target_idx": 3}
{"id": "mod_basicpy_0", "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": {"vizgenpostprocessing/compiletilesegmentation": "The module compiles segmentation tiles using Vizgen's post-processing tool.", "basicpy": "BaSiCPy is a python package for background and shading correction of optical microscopy images. It is develope", "utils_nfschema_plugin": "Run nf-schema to validate parameters and create a summary of changed parameters", "rrnatranscripts": "Ribosomal RNA extraction from a GTF file.", "vizgenpostprocessing/runsegmentationontile": "The module runs the segmentation algorithm on a specific tile using Vizgen's\npost-processing tool."}}, "target": "basicpy", "target_idx": 1}
{"id": "field_constraint_status_0_5", "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, "enum: [0, 1] (0=normal, 1=tumor)": null, "pattern: ^[A-Z]+$": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 2}
{"id": "resource_bedtools_closest_2", "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": "samplesheet_arch_pediatric_trio_somatic_1_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": "Which columns should the samplesheet have for Pediatric cancer trio (Child Proband tumor, Proband germline, Parents)?", "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_picard_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: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"octopusv/clean": null, "picard/cleansam": null, "hostile/clean": null, "pairtools/merge": null, "velocyto": null}}, "target": "picard/cleansam", "target_idx": 1}
{"id": "samplesheet_arch_amplicon_16s_paired_3_4", "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": "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": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "resource_aria2_3", "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_medium": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_samtools_markdup_0", "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": {"anarcii": "A language model for antigen receptor numbering", "bamclipper": "This module is used to clip primer sequences from your alignments.", "samtools/markdup": "mark duplicate alignments in a coordinate sorted file", "meryl/count": "A genomic k-mer counter (and sequence utility) with nice features.", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files."}}, "target": "samtools/markdup", "target_idx": 2}
{"id": "mod_minia_1", "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": {"busco_plot": "BUSCO summary plot generation using the built-in 'busco --plot' command", "seqkit_fq2fa": "Convert FASTQ to FASTA format", "bwa_sampe": "Convert paired-end bwa SA coordinate files to SAM format", "minia": "Minia is a short-read assembler based on a de Bruijn graph", "bwa_samse": "Convert bwa SA coordinate file to SAM format"}}, "target": "minia", "target_idx": 3}
{"id": "mod_doubletdetection_0", "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": {"gcta/keep": null, "cellbender/removebackground": null, "cellbender/merge": null, "shasta": null, "doubletdetection": null}}, "target": "doubletdetection", "target_idx": 4}
{"id": "qc_adapt_ont_ultra_long_0_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": "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": "samplesheet_arch_ont_metagenome_single_5_4", "category": "samplesheet_schema", "state": {"assay": "Long-read Oxford Nanopore environmental metagenomic sequencing", "first_step": "NANOPLOT"}, "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,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": "mod_cnvkit_access_0", "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": {"merquryfk/hapmaker": "Produces maternal and paternal FastK kmer tables from maternal, paternal and child\nFastK tables", "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.", "spring/compress": "Fast, efficient, lossless compression of FASTQ files.", "cnvkit/access": "Calculate the sequence-accessible coordinates in chromosomes from the given reference genome, output as a BED "}}, "target": "cnvkit/access", "target_idx": 4}
{"id": "qc_adapt_bulk_multiqc_2_33", "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_bedtools_jaccard_1", "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": {"bcftools_call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "bedtools_jaccard": "Calculate Jaccard statistic b/w two feature files.", "atlas_call": "generate VCF file from a BAM file using various calling methods", "lima": "lima - The PacBio Barcode Demultiplexer and Primer Remover", "purecn_run": "Run PureCN workflow to normalize, segment and determine purity and ploidy"}}, "target": "bedtools_jaccard", "target_idx": 1}
{"id": "resource_agat_spflagshortintrons_4", "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_single": null, "process_high": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_admixture_0", "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": {"somalier/ancestry": "Somalier can extract informative sites, evaluate relatedness, and perform quality-control on BAM/CRAM/BCF/VCF/", "admixture": "ADMIXTURE is a program for estimating ancestry in a model-based manner from large autosomal SNP genotype datas", "gcta/bivariatereml": "Run bivariate REML analysis with a single dense GRM", "angsd/contamination": "A tool to estimate nuclear contamination in males based on heterozygosity in the female chromosome.", "bamstats/generalstats": "write your description here"}}, "target": "admixture", "target_idx": 1}
{"id": "resource_biobambam_bamsormadup_3", "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_single": null, "process_high": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_gcta_makegrmpart_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compute one partition of a GCTA genetic relationship matrix (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", "bam_docounts_contamination_angsd": "Calculate contamination of the X-chromosome with ANGSD", "gcta_makegrmpart": "Compute one partition of a GCTA genetic relationship matrix", "gcta_addgrms": "Combine multiple GRMs listed in an MGRM manifest into a single dense GRM", "drep_dereplicate": "Dereplicates a genome  set by identifying highly similar genomes and choose the best representative genome"}}, "target": "gcta_makegrmpart", "target_idx": 2}
{"id": "noul_channel_join_operator_5", "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_gtfsort_1", "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": "Sort GTF files in chr/pos/feature order", "biobambam_bamsormadup": "Parallel sorting and duplicate marking", "doubletdetection": "Doublet detection in single-cell RNA-seq data", "clame": "binning of metagenomic sequences", "pyclonevi": "PyClone-VI is a software for inferring the clonal population structure of cancers by using variant allele freq"}}, "target": "gtfsort", "target_idx": 0}
{"id": "mod_plotsr_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Plotsr generates high-quality visualisation of synteny and structural rearrangements between multiple genomes. (tools: plotsr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_spfilterfeaturefromkilllist": null, "paragraph_vcf2paragraph": null, "agat_spmergeannotations": null, "plotsr": null, "juicertools_pre": null}}, "target": "plotsr", "target_idx": 3}
{"id": "noul_process_conditional_execution_24", "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": "pipe_all101_imcyto_0", "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": {"funcscan": null, "epitopeprediction": null, "genomeassembler": null, "chipseq": null, "magmap": null, "seqsubmit": null, "createtaxdb": null, "imcyto": null}}, "target": "imcyto", "target_idx": 7}
{"id": "mod_pridepy_fetchsdrf_1", "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": {"sentieon_dnascope": "DNAscope algorithm performs an improved version of Haplotype variant calling.", "diamond_linclust": "Fast protein sequence clustering using a greedy incremental approach", "blobtk_snail": "Creates blobtk snail plots.", "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."}}, "target": "pridepy_fetchsdrf", "target_idx": 4}
{"id": "mod_gapseq_doall_0", "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": {"openms/idmerger": null, "gapseq/doall": null, "gapseq/medium": null, "parabricks/starfusion": null, "carveme/carve": null}}, "target": "gapseq/doall", "target_idx": 1}
{"id": "mod_dragen_germline_0", "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_fastqc_umitools_trimgalore": "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", "dia_proteomics_analysis": "Complete DIA-NN proteomics analysis pipeline including in-silico library generation,\npreliminary analysis, emp", "picard/fastqtosam": "Converts a FASTQ file to an unaligned BAM or SAM file.", "hificnv": "Copy number variant calling from PacBio HiFi reads"}}, "target": "dragen/germline", "target_idx": 1}
{"id": "qc_adapt_targeted_amplicon_2_30", "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_rnaseq_se_2_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 should the input samplesheet have?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,vcf": null, "sample,fastq_1,strandedness": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 3}
{"id": "mod_ribotish_quality_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": {"ribotish_quality": "Quality control of riboseq bam data", "plastid_metagenegenerate": "Compute a metagene profile of read alignments, counts, or quantitative data over one or more regions of intere", "bigslice_downloaddb": "Downloads and extracts the BiG-SLiCE HMM database (biosynthetic and sub Pfams)\nusing the bundled `download_big", "gedi_price": "Identify translated ORFs from Ribo-seq BAMs using the PRICE algorithm", "racon": "Consensus module for raw de novo DNA assembly of long uncorrected reads"}}, "target": "ribotish_quality", "target_idx": 0}
{"id": "samplesheet_arch_bulk_small_rna_6_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 are standard for Small RNA / miRNA sequencing input samplesheet?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,mirna_id": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "mod_ngscheckmate_ncm_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Determining whether sequencing data comes from the same individual by using SNP matching. Designed for humans on vcf or bam files. (tools: ngscheckmate)?", "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", "controlfreec/freec2bed": "Plot Freec output", "ngscheckmate/ncm": "Determining whether sequencing data comes from the same individual by using SNP matching. Designed for humans ", "fastq_ngscheckmate": "Take a set of fastq files and run NGSCheckMate to determine whether samples match with each other, using a set", "bam_ngscheckmate": "Take a set of bam files and run NGSCheckMate to determine whether samples match with each other, using a set o"}}, "target": "ngscheckmate/ncm", "target_idx": 2}
{"id": "samplesheet_arch_cageseq_transcription_4_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": "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": null, "sample,bam": null, "sample,vcf": null, "sample,tss_bed": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "samplesheet_arch_scrna_multiome_1_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": "Which columns should the 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,matrix": null, "sample,fastq_1,fastq_2,feature_type": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 3}
{"id": "noul_modifying_channel_meta_inside_bash_script_block_19", "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_mgnifam_generatefamilies_1", "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": {"mgnifam_generatefamilies": null, "catpack_download": null, "traitar_run": null, "hmmer_hmmfetch": null, "samtools_bam2fq": null}}, "target": "mgnifam_generatefamilies", "target_idx": 0}
{"id": "qc_adapt_targeted_amplicon_0_11", "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": "resource_agat_spstatistics_0", "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_medium": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_biscuit_align_5", "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_low": null, "process_long": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_macs2_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: macs2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"macs2/callpeak": "Peak calling of enriched genomic regions of ChIP-seq and ATAC-seq experiments", "busco/phylogenomics": "Construct species phylogenies using BUSCO proteins", "gatk/indelrealigner": "Performs local realignment around indels to correct for mapping errors", "gatk4/mergevcfs": "Merges several vcf files", "ashlar": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration"}}, "target": "macs2/callpeak", "target_idx": 0}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_2_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 should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1": null, "sample,vcf": null}}, "target": "sample,bam", "target_idx": 1}
{"id": "samplesheet_arch_chipseq_with_control_0_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: ChIP-seq with IP and input control design?", "criteria": {"sample,fastq_1": 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_checkv_endtoend_0", "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": {"checkm/qa": "CheckM provides a set of tools for assessing the quality of genomes recovered from isolates, single cells, or ", "mapad/map": "Map short-reads to an indexed reference genome", "gstama/collapse": "Collapse redundant transcript models in Iso-Seq data.", "checkv/endtoend": "Assess the quality of metagenome-assembled viral genomes.", "checkm2/databasedownload": "CheckM2 database download"}}, "target": "checkv/endtoend", "target_idx": 3}
{"id": "samplesheet_arch_pediatric_trio_somatic_4_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": "What samplesheet columns are expected when inputs are: Paired-end FASTQs tracking patient, sample, tissue status (normal/tumor), and maternal/paternal lineage?", "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": "qc_adapt_ont_ultra_long_2_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": "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": "resource_biohansel_2", "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_long": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_angsd_contamination_0", "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_high": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_last_lastal_1", "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": {"popscle_freemuxlet": "Software to deconvolute sample identity and identify multiplets when multiple samples are pooled by barcoded s", "last_lastal": "Aligns query sequences to target sequences indexed with lastdb", "last_lastdb": "Prepare sequences for subsequent alignment with lastal.", "circularmapper_realignsamfile": "Realign reads mapped with BWA to elongated reference genome", "last_dotplot": "Makes a dotplot (Oxford Grid) of pair-wise sequence alignments"}}, "target": "last_lastal", "target_idx": 1}
{"id": "qc_adapt_singlecell_multiqc_2_38", "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": "qc_adapt_bulk_multiqc_0_21", "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": "mod_dragmap_hashtable_0", "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": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode.", "macs3/callpeak": "Peak calling of enriched genomic regions of ChIP-seq and ATAC-seq experiments", "samtools/sormadup": "Collate/Fixmate/Sort/Markdup SAM/BAM/CRAM file", "dragmap/hashtable": "Create DRAGEN hashtable for reference genome", "bcftools/index": "Index VCF tools"}}, "target": "dragmap/hashtable", "target_idx": 3}
{"id": "noul_deprecated_dsl1_set_keyword_19", "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_blast_tblastn_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": {"any2fasta": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input ", "parabricks_fq2bammeth": "NVIDIA Clara Parabricks GPU-accelerated fast, accurate algorithm for mapping methylated DNA sequence reads to ", "agat_spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "blast_tblastn": "Queries a BLAST DNA database", "gffcompare": "Compare, merge, annotate and estimate accuracy of generated gtf files"}}, "target": "blast_tblastn", "target_idx": 3}
{"id": "resource_busco_phylogenomics_5", "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_long": null, "process_high": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_antismash_antismash_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: antismash)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samtools_cramsize": "List CRAM Content-ID and Data-Series sizes", "antismash_antismash": "antiSMASH allows the rapid genome-wide identification, annotation\nand analysis of secondary metabolite biosynt", "antismash_antismashlitedownloaddatabases": "antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynt", "bigscape_bigscape": "BiG-SCAPE (Biosynthetic Gene Similarity Clustering and Prospecting Engine) clusters\nbiosynthetic gene clusters", "cellrangeratac_mkref": "Module to build the reference needed by the 10x Genomics Cell Ranger ATAC tool. Uses the cellranger-atac mkref"}}, "target": "antismash_antismash", "target_idx": 1}
{"id": "field_constraint_bai_1_12", "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$": null, "type: boolean": null, "pattern: ^\\S+\\.crai$": null, "pattern: ^\\S+\\.tbi$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 0}
{"id": "mod_hisat2_extractsplicesites_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extracts splicing sites from a gtf files (tools: hisat2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hisat2_extractsplicesites": "Extracts splicing sites from a gtf files", "regtools_junctionsextract": "Extract exon-exon junctions from an RNAseq BAM file. The output is a BED file in the BED12 format.", "fastq_download_prefetch_fasterqdump_sratools": "Download FASTQ sequencing reads from the NCBI's Sequence Read Archive (SRA).", "simpleaf_index": "Indexing of transcriptome for gene expression quantification using SimpleAF", "ctatsplicing_startocancerintrons": "Detection and annotation of aberrant splicing isoforms in cancer transcriptomes"}}, "target": "hisat2_extractsplicesites", "target_idx": 0}
{"id": "qc_adapt_singlecell_multiqc_0_1", "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": "schema_std_omicsgenetraitassociation_0_1", "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,fastq_1,fastq_2,rundir,tags": null, "sample,fastq_1,fastq_2,vcf": null, "sample,fastq_1,fastq_2,strandedness,type": null}}, "target": "sample,trait,pascal,twas,additional_sources", "target_idx": 0}
{"id": "noul_subworkflow_structural_blocks_5", "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_cancer_longitudinal_5_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": "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, "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_manta_germline_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": {"ctatsplicing/prepgenomelib": "Reference preparation for CTAT-splicing", "manta/germline": "Manta calls structural variants (SVs) and indels from mapped paired-end sequencing reads. It is optimized for ", "controlfreec/makegraph": "Plot Freec output", "controlfreec/assesssignificance": "Add both Wilcoxon test and Kolmogorov-Smirnov test p-values to each CNV output of FREEC", "hifiasm": "Whole-genome assembly using PacBio HiFi reads"}}, "target": "manta/germline", "target_idx": 1}
{"id": "pipe_all101_bactmap_0", "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": {"nascent": null, "hgtseq": null, "lsmquant": null, "slamseq": null, "bactmap": null, "variantbenchmarking": null, "proteogenomicsdb": null, "marsseq": null}}, "target": "bactmap", "target_idx": 4}
{"id": "resource_bedops_convert2bed_0", "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_medium": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_oncocnv_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calls CNVs in bam files from tumor patients (tools: oncocnv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"oncocnv": "Calls CNVs in bam files from tumor patients", "samtools_samples": "Write sample names and path to reference genome of an alignment to a text file.", "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.", "jvarkit_sam2tsv": "Convert sam files to tsv files"}}, "target": "oncocnv", "target_idx": 0}
{"id": "local_subworkflow_checkirma_1_5", "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, "Leave them out": null, "Local subworkflow CHECKIRMA": null, "Use nf-core subworkflow checkirma": null}}, "target": "Local subworkflow CHECKIRMA", "target_idx": 2}
{"id": "schema_std_oncoanalyser_1_0", "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,bam,vcf,rna_matrix,hto_matrix": null, "sample,trait,pascal,twas,additional_sources": null, "sample_id,group_id,subject_id,sample_type,sequence_type": null, "sample,group,ref_fasta,ref_gff,use_ref": null}}, "target": "sample_id,group_id,subject_id,sample_type,sequence_type", "target_idx": 2}
{"id": "mod_mash_screen_1", "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": {"sourmash_compare": "Compare many FracMinHash signatures generated by sourmash sketch.", "wget": "The non-interactive network downloader", "sourmash_gather": "Search a metagenome sourmash signature against one or many reference databases and return the minimum set of g", "bamutil_clipoverlap": "clips overlapping read pairs. When two mates overlap, this tool will clip the record's whose clipped region wo", "mash_screen": "Screens query sequences against large sequence databases"}}, "target": "mash_screen", "target_idx": 4}
{"id": "samplesheet_arch_vcf_annotation_pipeline_5_3", "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": "In Nextflow pipeline nf-core/raredisease, determine the input samplesheet column structure for: Downstream functional annotation of pre-called VCF files.", "criteria": {"sample,bam,bai": null, "sample,vcf,tbi": null, "sample,bed": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,vcf,tbi", "target_idx": 1}
{"id": "mod_metabat2_jgisummarizebamcontigdepths_0", "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": {"duphold": "SV callers like lumpy look at split-reads and pair distances to find structural variants. This tool is a fast ", "metabat2/jgisummarizebamcontigdepths": "Depth computation per contig step of metabat2", "custom/clustervisualization": "Generates UMAP and t-SNE visualizations colored by cluster", "glimpse2/concordance": "Program to compute the genotyping error rate at the sample or marker level.", "crisprcleanr/normalize": "remove false positives of functional crispr genomics due to CNVs"}}, "target": "metabat2/jgisummarizebamcontigdepths", "target_idx": 1}
{"id": "pipe_all101_proteinfold_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: 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": {"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]", "seqinspector": "Dedicated QC-only pipeline for sequencing data. The pipeline will run a (potentially large) set of QC tools and can outp", "viralmetagenome": "A nf-core pipeline for untargeted whole genome reconstruction with iSNV detection from metagenomic samples.  [epidemiolo", "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]", "proteogenomicsdb": "The ProteoGenomics database generation workflow creates different protein databases for ProteoGenomics data analysis. [c", "kmermaid": " k-mer similarity analysis pipeline [k-mer, kmer, kmer-counting]", "proteinfold": "Protein 3D structure prediction pipeline [alphafold2, colabfold, esmfold]", "metatdenovo": "Assembly and annotation of metatranscriptomic or metagenomic data for prokaryotic, eukaryotic and viruses. [eukaryotes, "}}, "target": "proteinfold", "target_idx": 8}
{"id": "mod_cellranger_mkvdjref_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to build the VDJ reference needed by the 10x Genomics Cell Ranger tool. Uses the cellranger mkvdjref command. (tools: cellranger)?", "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", "last_lastdb": "Prepare sequences for subsequent alignment with lastal.", "cellranger_mkvdjref": "Module to build the VDJ reference needed by the 10x Genomics Cell Ranger tool. Uses the cellranger mkvdjref co", "gappa_examineassign": "assigns taxonomy to query sequences in phylogenetic placement output"}}, "target": "cellranger_mkvdjref", "target_idx": 3}
{"id": "mod_fastq_index_filter_deacon_0", "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": {"bbmap/filterbyname": null, "fastq_index_filter_deacon": null, "ultra/align": null, "bamcmp": null, "svim/alignment": null}}, "target": "fastq_index_filter_deacon", "target_idx": 1}
{"id": "qc_adapt_bulk_multiqc_0_0", "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, "Swap for NanoPlot": null, "Keep MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "qc_adapt_ffpe_wes_2_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": "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_checkqc_0", "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": "A simple program to parse Illumina NGS data and check it for quality criteria", "pcgr/getref": "Get reference to run Personal Cancer Genome Reporter (PCGR)", "art/illumina": "Simulation tool to generate synthetic Illumina next-generation sequencing reads", "seqtk/sample": "Subsample reads from FASTQ files", "cellranger/mkfastq": "Module to create FASTQs needed by the 10x Genomics Cell Ranger tool. Uses the cellranger mkfastq command."}}, "target": "checkqc", "target_idx": 0}
{"id": "resource_bakta_baktadbdownload_2", "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_long": null, "process_high": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_sambamba_depth_0", "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": {"jvarkit/wgscoverageplotter": "Plot whole genome coverage from BAM/CRAM file as SVG", "deeptools/bamcoverage": "This tool takes an alignment of reads or fragments as input (BAM file) and generates a coverage track (bigWig ", "fgumi/filter": "Filters consensus reads generated by simplex or duplex consensus calling.\nThis is a high-performance replaceme", "sambamba/depth": "Outputs a coverage file from bam files", "kraken2/build": "Builds Kraken2 database"}}, "target": "sambamba/depth", "target_idx": 3}
{"id": "resource_bcftools_annotate_5", "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_long": null, "process_single": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "resource_bedtools_groupby_4", "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_medium": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_ampir_2", "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_high": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_mira_influenza_sc2_3_3", "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": "Define the required samplesheet CSV header schema for Custom MIRA-NF Influenza / SC2 pipeline with entry step INPUT_CHECK.", "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": "resource_bbmap_repair_4", "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_high": null, "process_single": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_targeted_amplicon_1_43", "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": "samplesheet_arch_bulk_wes_pe_1_4", "category": "samplesheet_schema", "state": {"assay": "Paired-end Whole Exome Sequencing (WES) target capture", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Paired-end Whole Exome Sequencing (WES) target capture?", "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_anndata_barcodes_3", "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_high": null, "process_long": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_mashtree_0", "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": {"vt/decomposeblocksub": "Decomposes biallelic block substitutions into its constituent SNPs.", "mashtree": "Quickly create a tree using Mash distances", "mash/sketch": "Creates vastly reduced representations of sequences using MinHash", "abritamr/run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes", "annotsv/annotsv": "Annotation and Ranking of Structural Variation"}}, "target": "mashtree", "target_idx": 1}
{"id": "resource_ashlar_0", "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_long": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_whatshap_stats_1", "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": {"scoary": "Use pangenome outputs for GWAS", "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.", "last_split": "Find split or spliced alignments in a MAF file", "whatshap_stats": "Compute statistics from phased variant file using Whatshap"}}, "target": "whatshap_stats", "target_idx": 4}
{"id": "resource_annosine_5", "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_low": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_biobambam_bammarkduplicates2_3", "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_low": null, "process_medium": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_jvarkit_vcf2table_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert VCF to a user friendly table (tools: jvarkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gt/gff3": null, "annotsv/annotsv": null, "bcftools/call": null, "fastqscan": null, "jvarkit/vcf2table": null}}, "target": "jvarkit/vcf2table", "target_idx": 4}
{"id": "mod_imc2mc_1", "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": {"mcstaging_imc2mc": "Staging module for MCMICRO transforming Imaging Mass Cytometry .txt files to .tif files with OME-XML metadata.", "cobiontid_kmercounter": "A rust based tool based on Needletail's FASTA parser tallies k-mer counts\nfor large sequencing rounds. Written", "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", "gappa_examineheattree": "colours a phylogeny with placement densities"}}, "target": "imc2mc", "target_idx": 3}
{"id": "mod_pairtools_flip_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Flip pairs to get an upper-triangular matrix (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", "octopusv_merge": "Merge and harmonize structural variant calls from multiple samples.", "mm2plus_index": "Provides fasta index required by mm2plus alignment.", "pairtools_merge": "Merge multiple pairs/pairsam files", "opt_flip_track_stat": "Off-target probe detection"}}, "target": "pairtools_flip", "target_idx": 0}
{"id": "qc_adapt_ont_nanoplot_0_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": "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": "pipe_all101_sopa_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: 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": {"sopa": "Nextflow version of Sopa - spatial omics pipeline and analysis [segmentation, spatial-omics, spatial-proteomics]", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples [amplicon, artic, assembly]", "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", "oncoanalyser": "A comprehensive cancer DNA/RNA analysis and reporting pipeline [cancer, clinical, ctdna]"}}, "target": "sopa", "target_idx": 0}
{"id": "pipe_all101_circdna_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: 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": {"proteinfold": null, "seqsubmit": null, "funcscan": null, "nanoseq": null, "metaboigniter": null, "viralrecon": null, "sarek": null, "createtaxdb": null, "circdna": null, "mcmicro": null}}, "target": "circdna", "target_idx": 8}
{"id": "mod_ngsbits_bedcoverage_0", "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": {"coptr/map": "Maps the reads to the reference database", "agat/convertgff2bed": "Takes a GFF3 file and converts to a bed12 file", "bamtools/convert": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "pbtk/pbmerge": "Simple tool which merges several PacBio BAM files together", "ngsbits/bedcoverage": "Annotates a BED file with the average coverage of the regions from one or several BAM/CRAM file(s)."}}, "target": "ngsbits/bedcoverage", "target_idx": 4}
{"id": "mod_custom_tx2gene_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Make a transcript/gene mapping from a GTF and cross-reference with transcript quantifications. (tools: custom)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samtools_addreplacerg": "Adds or replaces read group (RG) tags in BAM/CRAM/SAM files", "agat_spkeeplongestisoform": "Filters GFF records to keep only the longest isoform per gene", "bioformats2raw": "Java application to convert image file formats, including .mrxs, to an intermediate Zarr structure compatible ", "custom_tx2gene": "Make a transcript/gene mapping from a GTF and cross-reference with transcript quantifications.", "summarizedexperiment_summarizedexperiment": "SummarizedExperiment container"}}, "target": "custom_tx2gene", "target_idx": 3}
{"id": "resource_angsd_contamination_1", "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_high": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_bbmap_filterbyname_1", "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_long": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "noul_channel_mix_operator_5", "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_bcl_demultiplex_0", "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, "Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow bcl_demultiplex": null}}, "target": "Use nf-core subworkflow bcl_demultiplex", "target_idx": 3}
{"id": "mod_coptr_estimate_0", "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": {"circularmapper/circulargenerator": "A method to improve mappings on circular genomes, using the BWA mapper.", "rseqc/readduplication": "Calculate read duplication rate", "coptr/estimate": "Calculates peak-to-through ratio (PTR) from metagenomic sequence data", "coptr/extract": "Computes the coverage map along the reference genome", "vamb/bin": "Variational autoencoder for metagenomic binning"}}, "target": "coptr/estimate", "target_idx": 2}
{"id": "qc_adapt_targeted_amplicon_1_31", "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": "local_subworkflow_variantsofint_2_3", "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, "Use nf-core subworkflow variantsofint": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Local subworkflow VARIANTSOFINT", "target_idx": 0}
{"id": "field_constraint_fastq_1_2_14", "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": "samplesheet_arch_spatial_xenium_0_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": "Which columns should the input samplesheet have for: 10x Xenium in situ subcellular spatial RNA transcriptomics?", "criteria": {"sample,image": 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_undeclared_process_file_inputs_3", "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": "noul_multiple_script_sections_invalid_4", "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": "samplesheet_arch_germline_lane_split_0_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": "Which columns should the input samplesheet have for: Multi-lane Illumina sequencing run of clinical samples?", "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": "mod_amrfinderplus_run_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": {"snpeff_snpeff": "Genetic variant annotation and functional effect prediction toolbox", "amrfinderplus_run": "Identify antimicrobial resistance in gene or protein sequences", "cnvkit_call": "Given segmented log2 ratio estimates (.cns), derive each segment’s absolute integer copy number", "abricate_summary": "Screen assemblies for antimicrobial resistance against multiple databases", "abritamr_run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes"}}, "target": "amrfinderplus_run", "target_idx": 1}
{"id": "mod_muscle5_super5_0", "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": {"muscle5/super5": null, "ampcombi": null, "mcstaging/phenoimager2mc": null, "biscuit/bsconv": null, "bbmap/align": null}}, "target": "muscle5/super5", "target_idx": 0}
{"id": "qc_adapt_bulk_multiqc_2_13", "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_mirtop_stats_1", "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": "mirtop counts generates a file with the minimal information about each sequence and the count data in columns ", "srst2_srst2": "Short Read Sequence Typing for Bacterial Pathogens is a program designed to take Illumina sequence data,\na MLS", "samtools_fastq": "Converts a SAM/BAM/CRAM file to FASTQ", "mirtop_stats": "mirtop gff gets the number of isomiRs and miRNAs annotated in the GFF file by isomiR category.", "mirtop_gff": "mirtop gff generates the GFF3 adapter format to capture miRNA variations"}}, "target": "mirtop_stats", "target_idx": 3}
{"id": "resource_atlas_splitmerge_2", "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_low": null, "process_high": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "field_constraint_fastq_1_0_5", "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": "qc_adapt_illumina_novaseq_2_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": "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_fastquorum_1_1", "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,group,ref_fasta,ref_gff,use_ref": null, "sample_id,mapped,index,file_type": null, "sample,fastq_1,fastq_2,library_id,lane": null, "ID,Sample,Condition,ReplicateFileName,Fasta": null}}, "target": "sample,fastq_1,fastq_2,library_id,lane", "target_idx": 2}
{"id": "mod_crisprcleanr_normalize_0", "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": {"bedtools/sort": "Sorts a feature file by chromosome and other criteria.", "gridss/gridss": "GRIDSS is a module software suite containing tools useful for the detection of genomic rearrangements.", "elprep/filter": "Filter, sort and markdup sam/bam files, with optional BQSR and variant calling.", "plasmidfinder": "Identify plasmids in bacterial sequences and assemblies", "crisprcleanr/normalize": "remove false positives of functional crispr genomics due to CNVs"}}, "target": "crisprcleanr/normalize", "target_idx": 4}
{"id": "samplesheet_arch_viral_ont_single_0_2", "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: Viral genome sequencing on Oxford Nanopore MinION / GridION?", "criteria": {"sample,fasta": null, "sample,fastq_1": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "resource_assemblyscan_3", "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_low": null, "process_medium": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_viral_ont_single_4_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": "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,bam": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "field_constraint_fastq_2_2_3", "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, "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_gcta_adjustgrm_1", "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": {"artic_aligntrim": "Standalone version of fieldbioinformatics aligntrim. Soft clips amplicon scheme primer sites in BAM/SAM files.", "gcta_calculateldscores": "Calculate LD scores with GCTA and derive GREML-LDMS SNP groups", "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`", "bbmap_clumpify": "Create 30% Smaller, Faster Gzipped Fastq Files. And remove duplicates"}}, "target": "gcta_adjustgrm", "target_idx": 3}
{"id": "field_constraint_fastq_2_1_5", "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$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null, "enum: [0, 1]": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 2}
{"id": "samplesheet_arch_bulk_rnaseq_se_2_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 should the input samplesheet have?", "criteria": {"sample,vcf": null, "sample,bam": null, "sample,fastq_1,strandedness": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 2}
{"id": "field_constraint_fastq_1_1_12", "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$": null, "type: integer": null, "enum: [auto, forward, reverse, unstranded]": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 3}
{"id": "resource_bwafastalign_mem_0", "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_high": null, "process_medium": null, "process_single": null}}, "target": "process_high", "target_idx": 1}
{"id": "mod_deepvariant_postprocessvariants_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": {"bcftools_consensus": "Compresses VCF files", "homer_pos2bed": "Converting from HOMER peak to BED file formats", "bedtools_intersect": "Allows one to screen for overlaps between two sets of genomic features.", "bcftools_call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "deepvariant_postprocessvariants": "DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generat"}}, "target": "deepvariant_postprocessvariants", "target_idx": 4}
{"id": "mod_seqkit_fx2tab_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert FASTA/Q to tabular format, and provide various information, like sequence length, GC content/GC skew. (tools: seqkit)?", "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 ", "seqkit_fx2tab": "Convert FASTA/Q to tabular format, and provide various information, like sequence length, GC content/GC skew.", "haplocheck": "Haplocheck detects contamination patterns in mtDNA AND WGS sequencing studies by analyzing\nthe mitochondrial D", "agrvate": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants", "plink_extract": "Subset plink bfiles with a text file of variant identifiers"}}, "target": "seqkit_fx2tab", "target_idx": 1}
{"id": "samplesheet_arch_ont_direct_rna_se_5_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": "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,vcf": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "schema_std_metaboigniter_1_1", "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,type,level,msfile": null, "ID,Sample,Condition,ReplicateFileName,Fasta": null, "sample,alleles,mhc_class,filename": null, "sample_id,name,description,path,path_2": null}}, "target": "sample,type,level,msfile", "target_idx": 0}
{"id": "qc_adapt_pacbio_hifi_2_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": "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": "pipe_core10_viralrecon_0_bare", "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": null, "mag": null, "eager": null, "atacseq": null, "sarek": null, "ampliseq": null, "viralrecon": null, "scrnaseq": null, "rnaseq": null, "chipseq": null}}, "target": "viralrecon", "target_idx": 6}
{"id": "samplesheet_arch_pacbio_hifi_wgs_7_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": "Which columns are standard for PacBio HiFi input samplesheet?", "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": "subworkflow_pkg_fastq_align_bowtie2_2", "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": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow fastq_align_bowtie2": null, "Local subworkflow FASTQ_ALIGN_BOWTIE2": null, "Leave them out": null}}, "target": "Use nf-core subworkflow fastq_align_bowtie2", "target_idx": 1}
{"id": "mod_rmats_prep_0", "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": {"hisat2/extractsplicesites": null, "rmats/prep": null, "nanomonsv/parse": null, "ctatsplicing/prepgenomelib": null, "gatk4/printsvevidence": null}}, "target": "rmats/prep", "target_idx": 1}
{"id": "samplesheet_arch_smartseq_plate_based_6_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 are standard for Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq input samplesheet?", "criteria": {"plate,well,sample,fastq_1,fastq_2": null, "plate,sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,matrix": null}}, "target": "plate,well,sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "samplesheet_arch_riboseq_profiling_0_2", "category": "samplesheet_schema", "state": {"assay": "Ribosome profiling (Ribo-seq) footprint sequencing", "first_step": "FASTQC"}, "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,fastq_1,strandedness": null, "sample,vcf": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 2}
{"id": "mod_gatk4_combinegvcfs_0", "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": null, "bcftools/convert": null, "gunc/mergecheckm": null, "gatk4/reblockgvcf": null, "nanomonsv/get": null}}, "target": "gatk4/combinegvcfs", "target_idx": 0}
{"id": "samplesheet_arch_metatranscriptome_denovo_4_2", "category": "samplesheet_schema", "state": {"assay": "Environmental community metatranscriptomics de novo assembly", "first_step": "FASTQC"}, "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,bam": 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": "schema_std_genomeqc_1_0", "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": {"ID,R1,R2,LongFastQ,Fast5": null, "id,fasta,sequence": null, "fasta,assembly,ncbi,gff,fastq": null, "fastq_1,fastq_2,batch,amp_batches,seq_batches": null}}, "target": "fasta,assembly,ncbi,gff,fastq", "target_idx": 2}
{"id": "qc_adapt_ont_ultra_long_1_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": "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_samtools_getrg_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": {"samtools_splitheader": "Extract header lines from a SAM/BAM/CRAM file into separate files depending on type", "samtools_getrg": "filter/convert SAM/BAM/CRAM file", "samtools_convert": "convert and then index CRAM -> BAM or BAM -> CRAM file", "trtools_dumpstr": "DumpSTR filters VCF files with TR genotypes, performing call-level and locus-level filtering, and outputs a fi", "metaspace_converter": "Export METASPACE datasets to AnnData and SpatialData objects"}}, "target": "samtools_getrg", "target_idx": 1}
{"id": "mod_picard_mergesamfiles_1", "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": {"biobambam_bammerge": "Merge a list of sorted bam files", "picard_mergesamfiles": "Merges multiple BAM files into a single file", "atlas_splitmerge": "split single end read groups by length and merge paired end reads", "refsolver_score": "Score a query sequence dictionary against a reference using ref-solver", "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": "picard_mergesamfiles", "target_idx": 1}
{"id": "mod_bam_tumor_only_somatic_variant_calling_gatk_0", "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": {"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", "gatk4/annotateintervals": "Annotates intervals with GC content, mappability, and segmental-duplication content", "nanocomp": "Compare multiple runs of long read sequencing data and alignments", "mirtop/counts": "mirtop counts generates a file with the minimal information about each sequence and the count data in columns "}}, "target": "bam_tumor_only_somatic_variant_calling_gatk", "target_idx": 0}
{"id": "samplesheet_arch_bulk_wes_pe_4_2", "category": "samplesheet_schema", "state": {"assay": "Paired-end Whole Exome Sequencing (WES) target capture", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end FASTQs from Agilent/Twist exome target capture?", "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": "mod_bcftools_isec_1", "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": {"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.", "bcftools_isec": "Apply set operations to VCF files", "samtools_dict": "Create a sequence dictionary file from a FASTA file", "glimpse2_concordance": "Program to compute the genotyping error rate at the sample or marker level."}}, "target": "bcftools_isec", "target_idx": 2}
{"id": "resource_ataqv_ataqv_3", "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_low": null, "process_medium": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "qc_adapt_qc_aggregate_1_32", "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": "resource_bbmap_pileup_5", "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_low": null, "process_high": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_fcsgx_rungx_0", "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": {"cooler/merge": "Merge multiple coolers with identical axes", "agat/convertspgff2gtf": "Converts a GFF/GTF file into a proper GTF file", "fcsgx/rungx": "Runs FCS-GX (Foreign Contamination Screen - Genome eXtractor) to screen and remove foreign contamination from ", "agat/convertbed2gff": "Takes a bed12 file and converts to a GFF3 file", "wisecondorx/newref": "Create a new reference using healthy reference samples"}}, "target": "fcsgx/rungx", "target_idx": 2}
{"id": "resource_ataqv_ataqv_0", "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_low": null, "process_medium": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_picard_addorreplacereadgroups_0", "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": {"kraken2/add": "Adds fasta files to a Kraken2 taxonomic database", "bff": "Generating cell hashing calls from a matrix of count data.", "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", "seqfu/check": "Evaluates the integrity of DNA FASTQ files"}}, "target": "picard/addorreplacereadgroups", "target_idx": 3}
{"id": "qc_adapt_singlecell_multiqc_2_32", "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": "intent_ask_question_23", "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, "debug_error": null, "prepare_data": null}}, "target": "ask_question", "target_idx": 1}
{"id": "samplesheet_arch_chipseq_with_control_0_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: ChIP-seq with IP and input control design?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2,antibody,control": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 3}
{"id": "field_constraint_expected_cells_1_11", "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, "type: integer, minimum: 100, maximum: 50000": null, "enum: [auto, single, paired]": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 2}
{"id": "samplesheet_arch_spatial_xenium_0_2", "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 input samplesheet have for: 10x Xenium in situ subcellular spatial RNA transcriptomics?", "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_21", "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_cfdna_liquid_biopsy_6_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 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,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": "field_constraint_bai_0_4", "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": "qc_adapt_pe_illumina_fastqc_2_7", "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": "resource_bandage_image_4", "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_medium": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_autocycler_combine_0", "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_long": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_somalier_extract_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": {"cnvkit/fix": "Combine the uncorrected target and antitarget coverage tables (.cnn) and correct for biases in regional covera", "somalier/ancestry": "Somalier can extract informative sites, evaluate relatedness, and perform quality-control on BAM/CRAM/BCF/VCF/", "somalier/extract": "Somalier can extract informative sites, evaluate relatedness, and perform quality-control on BAM/CRAM/BCF/VCF/", "ascat": "copy number profiles of tumour cells.", "rseqc/inferexperiment": "Infer strandedness from sequencing reads"}}, "target": "somalier/extract", "target_idx": 2}
{"id": "samplesheet_arch_taxprofiler_shotgun_4_2", "category": "samplesheet_schema", "state": {"assay": "Multi-taxonomic profiling of complex metagenomic shotgun reads", "first_step": "FASTQC"}, "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,fastq_2": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 0}
{"id": "samplesheet_arch_pacbio_hifi_wgs_6_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 are standard for Long-read Pacific Biosciences HiFi sequencing input samplesheet?", "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_bedtools_shuffle_4", "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_single": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "field_constraint_bam_2_6", "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+\\.f(ast)?q(\\.gz)?$": null, "format: uri": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 0}
{"id": "mod_gvcftools_extractvariants_1", "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": {"bbmap_bbduk": "Adapter and quality trimming of sequencing reads", "glnexus": "merge gVCF files and perform joint variant calling", "bcftools_convert": "Converts certain output formats to VCF", "bcftools_roh": "A program for detecting runs of homo/autozygosity. Only bi-allelic sites are considered.", "gvcftools_extractvariants": "Removes all non-variant blocks from a gVCF file to produce a smaller variant-only VCF file."}}, "target": "gvcftools_extractvariants", "target_idx": 4}
{"id": "samplesheet_arch_germline_lane_split_5_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": "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, "patient,sample,status,fastq_1,fastq_2": null, "lane,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_rohviz_2", "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_medium": null, "process_long": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "intent_ask_question_20", "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", "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": "ask_question", "target_idx": 1}
{"id": "resource_bases2fastq_1", "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_long": null, "process_single": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_ont_nanoplot_0_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": "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_deepvariant_makeexamples_0", "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": {"atlas/call": "generate VCF file from a BAM file using various calling methods", "deepvariant/makeexamples": "Transforms the input alignments to a format suitable for the deep neural network variant caller", "aardvark/merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF.", "stare": "Framework that scores enhancer–gene interactions using the Activity-By-Contact model and derives transcription", "eautils/fastqstats": "Calculate general and per-base statistics from FASTQ files"}}, "target": "deepvariant/makeexamples", "target_idx": 1}
{"id": "samplesheet_arch_viral_amplicon_artic_4_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": "What samplesheet columns are expected when inputs are: Paired-end tiled viral amplicon FASTQs per clinical swab sample?", "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_custom_orfcollapse_0", "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": {"custom/orfcollapse": "Collapse small ORFs that share an amino-acid sequence cluster into a single\ncatalogue entry. Pair with `custom", "gedi/indexgenome": "Build a GEDI genome index from a FASTA and GTF for downstream PRICE ORF prediction", "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", "gedi/price": "Identify translated ORFs from Ribo-seq BAMs using the PRICE algorithm", "upp/align": "Aligns protein structures using UPP"}}, "target": "custom/orfcollapse", "target_idx": 0}
{"id": "schema_std_proteinfamilies_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/proteinfamilies", "description": "Generation and updating of protein families", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/proteinfamilies?", "criteria": {"sample,condition,assay,peak_file,footprinting": null, "sample,nuclear_image,spot_table,membrane_image": null, "sample,fastq_1,fastq_2,strandedness,condition": null, "sample,fasta,existing_hmms_to_update,existing_msas_to_update": null}}, "target": "sample,fasta,existing_hmms_to_update,existing_msas_to_update", "target_idx": 3}
{"id": "mod_autocycler_cluster_1", "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": "Cluster replicons in compressed assemblies with Autocycler.", "genescopefk": "A derivative of GenomeScope2.0 modified to work with FastK", "autocycler_trim": "Trim cluster assembly graphs to remove unsupported segments prior to resolution.", "sourmash_compare": "Compare many FracMinHash signatures generated by sourmash sketch.", "autocycler_subsample": "Downsample long-read sequencing data to the requested coverage using Autocycler."}}, "target": "autocycler_cluster", "target_idx": 0}
{"id": "pipe_all101_viralmetagenome_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: 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": {"viralmetagenome": "A nf-core pipeline for untargeted whole genome reconstruction with iSNV detection from metagenomic samples.  [epidemiolo", "pathogensurveillance": "Surveillance of pathogens using population genomics and sequencing [biosurveillance, pathogen-identification]", "mcmicro": "An end-to-end processing pipeline that transforms multi-channel whole-slide images into single-cell data. [bioformats, i", "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]", "clipseq": "CLIP sequencing analysis pipeline for QC, pre-mapping, genome mapping, UMI deduplication, and multiple peak-calling opti", "hic": "Analysis of Chromosome Conformation Capture data (Hi-C) [chromosome-conformation-capture, hi-c]", "hadge": "Comprehensive pipeline for donor demultiplexing in single cell [cell-hashing, deconvolution, demultiplexing]"}}, "target": "viralmetagenome", "target_idx": 0}
{"id": "intent_build_pipeline_23", "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, "build_pipeline": null, "prepare_data": null}}, "target": "build_pipeline", "target_idx": 2}
{"id": "qc_adapt_singlecell_multiqc_0_38", "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": "pipe_all101_isoseq_0", "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": {"metatdenovo": null, "oncoanalyser": null, "dualrnaseq": null, "methylong": null, "diaproteomics": null, "mhcquant": null, "sarek": null, "metapep": null, "rangeland": null, "isoseq": null}}, "target": "isoseq", "target_idx": 9}
{"id": "mod_bowtie_align_1", "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": {"bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files.", "picard_markduplicates": "Locate and tag duplicate reads in a BAM file", "ampcombi2_complete": "A submodule that merges all output summary tables from ampcombi/parsetables in one summary file.", "bowtie_align": "Align reads to a reference genome using bowtie", "proseg_proseg2baysor": "Convert proseg outputs to baysor format for import to Xenium explorer"}}, "target": "bowtie_align", "target_idx": 3}
{"id": "subworkflow_pkg_fasta_vclust_prefilter_align_cluster_1", "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, "Local subworkflow FASTA_VCLUST_PREFILTER_ALIGN_CLUSTER": null, "Use nf-core subworkflow fasta_vclust_prefilter_align_cluster": null, "Leave them out": null}}, "target": "Use nf-core subworkflow fasta_vclust_prefilter_align_cluster", "target_idx": 2}
{"id": "pipe_all101_diaproteomics_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: 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": {"rnastructurome": "a bioinformatics pipeline for analysing chemical high-throughput RNA structure-probing data [dms, map, rna-structure]", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina", "rnasplice": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis [alternative-splicing, rna, rna-seq]", "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]", "denovotranscript": "A pipeline for de novo transcriptome assembly of paired-end short reads from bulk RNA-seq [denovo-assembly, rna-seq, tra", "metatdenovo": "Assembly and annotation of metatranscriptomic or metagenomic data for prokaryotic, eukaryotic and viruses. [eukaryotes, ", "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", "proteinfold": "Protein 3D structure prediction pipeline [alphafold2, colabfold, esmfold]"}}, "target": "diaproteomics", "target_idx": 8}
{"id": "resource_bwamem2_index_1", "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_low": null, "process_single": null, "process_medium": null}}, "target": "process_high", "target_idx": 0}
{"id": "mod_infernal_cmsearch_0", "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": {"whatshap/haplotag": null, "fastq_qc_trim_filter_setstrandedness": null, "infernal/cmsearch": null, "fastq_remove_rrna": null, "memote/report": null}}, "target": "infernal/cmsearch", "target_idx": 2}
{"id": "qc_adapt_bulk_multiqc_2_7", "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": "samplesheet_arch_bulk_wes_pe_1_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": "Which columns should the samplesheet have for Paired-end Whole Exome Sequencing (WES) target capture?", "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": "resource_angsd_contamination_5", "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_high": null, "process_low": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_samtools_collatefastq_1", "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": {"cpc2": "Coding Potential Calculator 2", "samtools_collatefastq": "The module uses collate and then fastq methods from samtools to\nconvert a SAM, BAM or CRAM file to FASTQ forma", "cnvkit_antitarget": "Derive off-target (“antitarget”) bins from target regions.", "rustqc": "All-in-one RNA-seq post-alignment QC replacing dupRadar, featureCounts biotype QC, RSeQC, Preseq, Qualimap, an", "samtools_bam2fq": "The module uses bam2fq method from samtools to\nconvert a SAM, BAM or CRAM file to FASTQ format"}}, "target": "samtools_collatefastq", "target_idx": 1}
{"id": "mod_bamutil_trimbam_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: trims the end of reads in a SAM/BAM file, changing read ends to ‘N’ and quality to ‘!’, or by soft clipping (tools: bamutil)?", "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", "bamclipper": "This module is used to clip primer sequences from your alignments.", "bamutil/trimbam": "trims the end of reads in a SAM/BAM file, changing read ends to ‘N’ and quality to ‘!’, or by soft clipping", "simpleaf/quant": "simpleaf is a program to simplify and customize the running and configuration of single-cell processing with a", "atlas/pmd": "Estimate the post-mortem damage patterns of DNA"}}, "target": "bamutil/trimbam", "target_idx": 2}
{"id": "local_subworkflow_nextclade_2_5", "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, "Use nf-core subworkflow nextclade": null, "Local subworkflow NEXTCLADE": null, "Keep the modules in the main workflow": null}}, "target": "Local subworkflow NEXTCLADE", "target_idx": 2}
{"id": "pipe_all101_epitopeprediction_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: 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": {"pacvar": null, "fastquorum": null, "raredisease": null, "epitopeprediction": null, "seqsubmit": null}}, "target": "epitopeprediction", "target_idx": 3}
{"id": "schema_std_scnanoseq_2_1", "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": {"RNA_ID,RNA_BAM_FILE,RNA_BAI_FILE,DNA_ID,DNA_VCF_FILE": null, "sample,fastq,cell_count": null, "fasta,assembly,ncbi,gff,fastq": null, "sample,vcf,tbi": null}}, "target": "sample,fastq,cell_count", "target_idx": 1}
{"id": "mod_t1k_build_0", "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": {"cmseq/polymut": "Calculates polymorphic site rates over protein coding genes", "bedtools/genomecov": "Computes histograms (default), per-base reports (-d) and BEDGRAPH (-bg) summaries of feature coverage (e.g., a", "dragmap/hashtable": "Create DRAGEN hashtable for reference genome", "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."}}, "target": "t1k/build", "target_idx": 4}
{"id": "schema_std_detaxizer_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/detaxizer", "assay": "detaxizer pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/detaxizer (A pipeline to identify (and remove) certain sequences from r)?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "id,test_vcf,test_regions,caller,subsample": null, "sample,short_reads_fastq_1,short_reads_fastq_2,long_reads_fastq_1": null, "sample,group,ref_fasta,ref_gff,use_ref": null}}, "target": "sample,short_reads_fastq_1,short_reads_fastq_2,long_reads_fastq_1", "target_idx": 2}
{"id": "noul_retry_errorstrategy_6", "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_deeptools_bamcoverage_0", "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": {"biobambam/bamsormadup": "Parallel sorting and duplicate marking", "rattle/cluster": "Reference-free reconstruction and quantification of transcriptomes from long-read sequencing", "bbmap/pileup": "Calculates per-scaffold or per-base coverage information from an unsorted sam or bam file.", "deeptools/bamcoverage": "This tool takes an alignment of reads or fragments as input (BAM file) and generates a coverage track (bigWig ", "allelecounter": "Generates a count of coverage of alleles"}}, "target": "deeptools/bamcoverage", "target_idx": 3}
{"id": "noul_channel_join_operator_18", "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": "qc_adapt_qc_aggregate_1_25", "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": "noul_channel_join_operator_10", "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": "resource_bbmap_bbsplit_2", "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_medium": null, "process_single": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_varlociraptor_filterfdr_1", "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": {"varlociraptor_filterfdr": "Filter Varlociraptor variant calls using FDR control.", "aardvark_compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "riker_multi": "Run multiple riker collectors in a single BAM pass using riker multi. Specify\ntools via ext.args (e.g. '--tool", "bcftools_annotate": "Add or remove annotations.", "cooler_digest": "Generate fragment-delimited genomic bins"}}, "target": "varlociraptor_filterfdr", "target_idx": 0}
{"id": "qc_adapt_pe_illumina_fastqc_0_7", "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_viral_amplicon_artic_1_2", "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 samplesheet have for Viral amplicon sequencing with primers?", "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": "mod_deepvariant_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": {"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", "aardvark_compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "custom_pcaclustering": "Performs KMeans or DBSCAN clustering on a sample-by-feature numeric matrix (e.g. principal components, embeddi", "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": "deepvariant", "target_idx": 0}
{"id": "mod_xz_compress_1", "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": "Decompression tool for foldcomp compressed structures", "rtgtools_vcfeval": "The VCFeval tool of RTG tools. It is used to evaluate called variants for agreement with a baseline variant se", "xz_compress": "Compresses files with xz.", "gunzip": "Compresses and decompresses files.", "krakenuniq_build": "Download and build (custom) KrakenUniq databases"}}, "target": "xz_compress", "target_idx": 2}
{"id": "pipe_all101_mnaseseq_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for mnase-seq. 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. ", "createpanelrefs": "Generate Panel of Normals, models or other similar references from lots of samples", "slamseq": "SLAMSeq processing and analysis pipeline [differential-expression, quantseq, slamseq]", "mnaseseq": "MNase-seq analysis pipeline using BWA and DANPOS2. [mnase-seq, nucleosome, nucleosome-maps]", "reportho": "nf-core pipeline for comparative analysis of ortholog predictions [ortholog]", "viralintegration": "Analysis pipeline for the identification of viral integration events in genomes using a chimeric read approach. [chimeri", "molkart": "A pipeline for processing Molecular Cartography data from Resolve Bioscience (combinatorial FISH) [fish, image-processin", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina"}}, "target": "mnaseseq", "target_idx": 3}
{"id": "field_constraint_strandedness_3_2", "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": "mod_endorspy_1", "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": {"hmmer_eslalipid": "Calculate pairwise percent identity for all sequence pairs in a multiple sequence alignment", "damageprofiler": "A Java based tool to determine damage patterns on ancient DNA as a replacement for mapDamage", "mashmap": "Mashmap is an approximate long read or contig mapper based on Jaccard similarity", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "endorspy": "endorS.py calculates endogenous DNA from samtools flagstat files and print to screen"}}, "target": "endorspy", "target_idx": 4}
{"id": "resource_bedtools_getfasta_2", "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_low": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_targeted_amplicon_0_19", "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": "schema_std_proteinfold_2_0", "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": {"fastq_1,fastq_2,batch,amp_batches,seq_batches": null, "sample,fastq_1,fastq_2,umi_barcodes": null, "sample,fastq_1,fastq_2": null, "id,fasta,sequence": null}}, "target": "id,fasta,sequence", "target_idx": 3}
{"id": "qc_adapt_bulk_multiqc_0_48", "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 MultiQC": null, "Keep FastQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "field_constraint_phenotype_3_3", "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, "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": "noul_workflow_completion_lifecycle_hook_14", "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": "pipe_all101_chipseq_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: ChIP-seq peak-calling, QC and differential analysis pipeline.. Topics: chip, chip-seq, chromatin-immunoprecipitation, macs2, peak-calling. ?", "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]", "methylseq": "Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair [bisulfi", "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", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples [amplicon, artic, assembly]", "coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]", "differentialabundance": "Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq  [atac-seq, chip-seq, d", "demultiplex": "Demultiplexing pipeline for sequencing data [bases2fastq, bcl2fastq, demultiplexing]"}}, "target": "chipseq", "target_idx": 2}
{"id": "mod_bedtools_shift_0", "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": {"agat/convertbed2gff": "Takes a bed12 file and converts to a GFF3 file", "quantify_pseudo_alignment": "Perform quantification with Salmon or Kallisto to produce count tables and SummarizedExperiment objects", "bedtools/shift": "Shifts each feature by specific number of bases", "crispresso2": "A software pipeline for the analysis of genome editing outcomes from deep sequencing data", "agat/convertgff2bed": "Takes a GFF3 file and converts to a bed12 file"}}, "target": "bedtools/shift", "target_idx": 2}
{"id": "subworkflow_pkg_vcf_extract_relate_somalier_1", "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": {"Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow VCF_EXTRACT_RELATE_SOMALIER": null, "Use nf-core subworkflow vcf_extract_relate_somalier": null}}, "target": "Use nf-core subworkflow vcf_extract_relate_somalier", "target_idx": 3}
{"id": "mod_sourmash_compare_1", "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": {"sylph_profile": "Sylph profile command for taxonoming profiling", "sourmash_compare": "Compare many FracMinHash signatures generated by sourmash sketch.", "instrain_compare": "Strain-level comparisons across multiple inStrain profiles", "gtfsort": "Sort GTF files in chr/pos/feature order", "deeptools_bigwigcompare": "Compare two bigWig files based on the number of mapped reads"}}, "target": "sourmash_compare", "target_idx": 1}
{"id": "mod_gamma_gamma_0", "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": {"macse/refinealignment": "improves the input nucleotide alignment in a codon-aware manner", "prodigal": "Prodigal (Prokaryotic Dynamic Programming Genefinding Algorithm) is a microbial (bacterial and archaeal) gene ", "allelecounter": "Generates a count of coverage of alleles", "gamma/gamma": "Gene Allele Mutation Microbial Assessment", "parsnp": "Parsnp is a command-line-tool for efficient microbial core genome alignment and SNP detection."}}, "target": "gamma/gamma", "target_idx": 3}
{"id": "schema_std_viralrecon_2_1", "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": {"patient,vcf,tbi,dataset,tumour_sample": null, "condition,type,microbiome_path,alleles,weights_path": null, "sample,fastq_1,fastq_2,rundir,tags": null, "sample,fastq_1,fastq_2,barcode": null}}, "target": "sample,fastq_1,fastq_2,barcode", "target_idx": 3}
{"id": "subworkflow_pkg_bedgraph_bedclip_bedgraphtobigwig_3", "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, "Use nf-core subworkflow bedgraph_bedclip_bedgraphtobigwig": null, "Local subworkflow BEDGRAPH_BEDCLIP_BEDGRAPHTOBIGWIG": null}}, "target": "Use nf-core subworkflow bedgraph_bedclip_bedgraphtobigwig", "target_idx": 2}
{"id": "samplesheet_arch_viral_ont_single_2_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 should the input samplesheet have?", "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_primerprospector_analyzeprimers_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Score PCR primers for binding to target sequences (tools: primerprospector)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abritamr_run": null, "qcat": null, "gem3_gem3indexer": null, "crabs_insilicopcr": null, "primerprospector_analyzeprimers": null}}, "target": "primerprospector_analyzeprimers", "target_idx": 4}
{"id": "resource_arriba_arriba_2", "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_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "resource_bbmap_bbnorm_1", "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_low": null, "process_long": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "field_constraint_bam_3_2", "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$": null, "format: uri": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 0}
{"id": "samplesheet_arch_prealigned_cram_indexed_3_2", "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": "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,bam,bai": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,cram,crai", "target_idx": 1}
{"id": "subworkflow_pkg_fastq_remove_rrna_0", "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": {"Use nf-core subworkflow fastq_remove_rrna": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow FASTQ_REMOVE_RRNA": null}}, "target": "Use nf-core subworkflow fastq_remove_rrna", "target_idx": 0}
{"id": "field_constraint_sample_2_12", "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, "pattern: ^\\S+$ (no whitespace, unique)": null, "enum: [0, 1]": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 2}
{"id": "field_constraint_bam_0_9", "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": "mod_suppa_psiperisoform_1", "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": {"agat_spfilterbyorfsize": null, "suppa_psiperisoform": null, "gget_gget": null, "agat_spextractsequences": null, "kaiju_mkfmi": null}}, "target": "suppa_psiperisoform", "target_idx": 1}
{"id": "samplesheet_arch_ancient_dna_eager_3_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": "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, "patient,sample,status,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": 0}
{"id": "mod_panacus_histgrowth_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculates a coverage histogram from a GFA file and constructs a growth table from this as either a TSV or HTML file (tools: panacus)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"last_mafswap": "Reorder alignments in a MAF file", "panacus_histgrowth": "Calculates a coverage histogram from a GFA file and constructs a growth table from this as either a TSV or HTM", "agat_spstatistics": "Provides different type of statistics in text format from a GFF/GTF annotation file", "eautils_fastqstats": "Calculate general and per-base statistics from FASTQ files", "oncocnv": "Calls CNVs in bam files from tumor patients"}}, "target": "panacus_histgrowth", "target_idx": 1}
{"id": "mod_busco_generateplot_1", "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": {"abacas": null, "busco_generateplot": null, "agat_convertspgff2tsv": null, "vt_decomposeblocksub": null, "fcsgx_rungx": null}}, "target": "busco_generateplot", "target_idx": 1}
{"id": "pipe_all101_scrnaseq_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: 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": null, "createpanelrefs": null, "ampliseq": null, "chipseq": null, "scrnaseq": null, "references": null, "dualrnaseq": null, "raredisease": null, "proteinannotator": null, "phaseimpute": null}}, "target": "scrnaseq", "target_idx": 4}
{"id": "mod_smoothxg_1", "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": {"porechop_abi": "Extension of Porechop whose purpose is to process adapter sequences in ONT reads.", "cooler_merge": "Merge multiple coolers with identical axes", "bandage_image": "Render an assembly graph in GFA 1.0 format to PNG and SVG image formats", "gfatools_gfa2fa": "Converts GFA or rGFA files to FASTA", "smoothxg": "Linearize and simplify variation graph in GFA format using blocked partial order alignment"}}, "target": "smoothxg", "target_idx": 4}
{"id": "qc_adapt_singlecell_multiqc_2_48", "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_bbmap_align_2", "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_low": null, "process_high": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "pipe_all101_methylong_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Extract methylation calls from long reads (ONT/ PacBio). Topics: dna-methylation, fiber-seq, long-read, ont, pacbio. . 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]", "fastquorum": "Pipeline to produce consensus reads using unique molecular indexes/barcodes (UMIs) [consensus, umi, umis]", "sopa": "Nextflow version of Sopa - spatial omics pipeline and analysis [segmentation, spatial-omics, spatial-proteomics]", "isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a", "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]", "raredisease": "Call and score variants from WGS/WES of rare disease patients. [diagnostics, rare-disease, snv]", "differentialabundance": "Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq  [atac-seq, chip-seq, d", "molkart": "A pipeline for processing Molecular Cartography data from Resolve Bioscience (combinatorial FISH) [fish, image-processin", "airrflow": "B-cell and T-cell Adaptive Immune Receptor Repertoire (AIRR) sequencing analysis pipeline using the Immcantation framewo"}}, "target": "methylong", "target_idx": 0}
{"id": "samplesheet_arch_spatial_visium_4_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": "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,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": "qc_adapt_pe_illumina_fastqc_0_9", "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_amrfinderplus_update_4", "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": "mod_rpbp_selectfinalpredictionset_1", "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_getperiodiclengthsoffsets": "Filter the per-read-length P-site offset table down to the\n(length, offset) pairs that will actually drive ORF", "rpbp_preparegenome": "Build the per-ORF reference files that Rp-Bp's downstream scoring needs,\nstarting from a genome FASTA and an a", "pear": "PEAR is an ultrafast, memory-efficient and highly accurate pair-end read merger.", "ncbigenomedownload": "A tool to quickly download assemblies from NCBI's Assembly database", "rpbp_selectfinalpredictionset": "Produce the final filtered set of predicted translated ORFs from the\nper-ORF Bayes factor table. Applies the s"}}, "target": "rpbp_selectfinalpredictionset", "target_idx": 4}
{"id": "noul_concurrent_writes_to_identical_work_dir_paths_3", "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_expected_cells_0_0", "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, "format: file-path": null, "pattern: ^\\S+\\.csv$": null, "enum: [auto, single, paired]": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 0}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_4_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": "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,fasta": null, "sample,fastq_1,fastq_2,long_fastq": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 3}
{"id": "resource_amrfinderplus_update_1", "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_medium": null, "process_high": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_viral_amplicon_artic_1_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": "Which columns should the samplesheet have for Viral amplicon sequencing with primers?", "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": "schema_std_references_1_1", "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": {"sample,type,level,msfile": null, "sample_id,idat_red,idat_green,group": null, "sample,fastq_1,fastq_2,group": null, "vcf,fasta,genome,site,source": null}}, "target": "vcf,fasta,genome,site,source", "target_idx": 3}
{"id": "mod_gatk4_preprocessintervals_0", "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": {"agat/convertgff2bed": "Takes a GFF3 file and converts to a bed12 file", "bamtools/convert": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "gatk4/preprocessintervals": "Prepares bins for coverage collection.", "mageck/mle": "maximum-likelihood analysis of gene essentialities computation", "circularmapper/circulargenerator": "A method to improve mappings on circular genomes, using the BWA mapper."}}, "target": "gatk4/preprocessintervals", "target_idx": 2}
{"id": "mod_ampcombi_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool to parse and summarise results from antimicrobial peptides tools and present functional classification. (tools: ampcombi)?", "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.", "samtools_bedcov": "reports coverage over regions in a supplied BED file", "famsa_guidetree": "Renders a guidetree in famsa", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "ampcombi2_parsetables": "A submodule that parses and standardizes the results from various antimicrobial peptide identification tools."}}, "target": "ampcombi", "target_idx": 0}
{"id": "noul_subworkflow_structural_blocks_4", "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_rpbp_getperiodiclengthsoffsets_0", "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": {"rpbp/preparegenome": "Build the per-ORF reference files that Rp-Bp's downstream scoring needs,\nstarting from a genome FASTA and an a", "rpbp/getperiodiclengthsoffsets": "Filter the per-read-length P-site offset table down to the\n(length, offset) pairs that will actually drive ORF", "rpbp/extractorfprofiles": "Build a per-ORF P-site count vector for every candidate open reading\nframe (ORF) in the catalogue. For each OR", "wittyer": "A large variant benchmarking tool analogous to hap.py for small variants.", "cdhit/cdhit": "Cluster protein sequences using sequence similarity"}}, "target": "rpbp/getperiodiclengthsoffsets", "target_idx": 1}
{"id": "subworkflow_pkg_bam_impute_quilt2_1", "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": {"Local subworkflow BAM_IMPUTE_QUILT2": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow bam_impute_quilt2": null, "Leave them out": null}}, "target": "Use nf-core subworkflow bam_impute_quilt2", "target_idx": 2}
{"id": "samplesheet_arch_singlecell_parse_splitseq_4_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": "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": null, "sample,well,plate": null}}, "target": "sample,subpool,fastq_1,fastq_2", "target_idx": 1}
{"id": "noul_deprecated_dsl1_set_keyword_10", "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": "resource_bedtools_flank_1", "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_long": null, "process_low": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_csvtk_concat_1", "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": {"csvtk_concat": "Concatenate two or more CSV (or TSV) tables into a single table", "jvarkit_vcffilterjdk": "Filtering VCF with dynamically-compiled java expressions", "qsv_cat": "Concatenate two or more CSV (or TSV) tables into a single table", "peka": "Runs PEKA CLIP peak k-mer analysis", "agat_convertspgff2tsv": "Converts a GFF/GTF file into a TSV file"}}, "target": "csvtk_concat", "target_idx": 0}
{"id": "schema_std_abotyper_2_1", "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,fastq_1,fastq_2,antibody,control": null, "sample,bam,vcf,rna_matrix,hto_matrix": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,genome": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "qc_adapt_ffpe_wes_2_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": "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_quast_bare_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": {"busco": null, "quast": null, "checkm": null, "mummer": null, "multiqc": null}}, "target": "quast", "target_idx": 1}
{"id": "mod_irescue_1", "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": {"fasta_index_bismark_bwameth": "Generate index files from reference fasta for bismark and bwameth", "irescue": "Quantification of transposable elements expression in scRNA-seq", "kallistobustools_count": "quantifies scRNA-seq data from fastq files using kb-python.", "cellbender_removebackground": "Module to use CellBender to estimate ambient RNA from single-cell RNA-seq data", "foldcomp_compress": "Efficient compression tool for protein structures"}}, "target": "irescue", "target_idx": 1}
{"id": "schema_std_pairgenomealign_1_0", "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, "RNA_ID,RNA_BAM_FILE,RNA_BAI_FILE,DNA_ID,DNA_VCF_FILE": null, "sample,fastq_1,fastq_2,bam,bai": null, "sample,fasta,protein,gbk,gff": null}}, "target": "sample,fasta", "target_idx": 0}
{"id": "samplesheet_arch_bulk_rnaseq_se_5_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": "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,vcf": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 0}
{"id": "mod_samtools_calmd_1", "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": {"abra2": null, "controlfreec_makegraph": null, "ascat": null, "samtools_calmd": null, "blast_blastn": null}}, "target": "samtools_calmd", "target_idx": 3}
{"id": "qc_adapt_ont_ultra_long_0_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": "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": "qc_adapt_targeted_amplicon_1_14", "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_vrhyme_linkbins_1", "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": "Linking bins output by vRhyme to create one sequences per bin", "comebin_runcomebin": "Effective binning of metagenomic contigs using COntrastive Multi-viEw representation learning", "gt_stat": "GenomeTools gt-stat utility to show statistics about features contained in GFF3 files", "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", "vrhyme_vrhyme": "Binning virus genomes from metagenomes"}}, "target": "vrhyme_linkbins", "target_idx": 0}
{"id": "resource_bamtools_split_0", "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_single": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "resource_autocycler_cluster_5", "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_single": null, "process_high": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "schema_std_longraredisease_1_0", "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,type,level,msfile": null, "sample,fasta": null, "SAMPLE_ID,RCC_FILE,RCC_FILE_NAME,TIME,TREATMENT": null, "family_id,sample,file_path,hpo_terms,sex": null}}, "target": "family_id,sample,file_path,hpo_terms,sex", "target_idx": 3}
{"id": "subworkflow_pkg_bam_telomere_estimation_1", "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": "mod_humann3_renorm_1", "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_humann": "Functional analysis of metagenome or metatranscriptome data", "transrate": "Reference-free and reference-based quality assessment of de novo transcriptome\nassemblies. Only sequence-based", "ucsc_liftover": "convert between genome builds", "humann3_renorm": "Normalizing RPKs to relative abundance", "humann3_regroup": "Regrouping genes to other functional categories"}}, "target": "humann3_renorm", "target_idx": 3}
{"id": "mod_jellyfish_count_1", "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": {"seqkit_head": "Subset FASTA/FASTQ files to some number of sequences", "scanpy_pca": "Perform principal component analysis (PCA) on single-cell RNA-seq data using Scanpy", "fastk_fastk": "A fast K-mer counter for high-fidelity shotgun datasets", "fastk_merge": "A tool to merge FastK histograms", "jellyfish_count": "Efficiently counts k-mers from DNA sequencing reads using a fast, memory-efficient, parallelized algorithm"}}, "target": "jellyfish_count", "target_idx": 4}
{"id": "resource_blast_tblastn_0", "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_long": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_metagenome_mag_grouped_1_1", "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 Metagenomic MAG assembly with comparative groups?", "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": "field_constraint_phenotype_1_0", "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, "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_tailfindr_0", "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": {"fastq_remove_rrna": null, "trtools/dumpstr": null, "emu/abundance": null, "tailfindr": null, "canu": null}}, "target": "tailfindr", "target_idx": 3}
{"id": "noul_subworkflow_structural_blocks_10", "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": "resource_bftools_showinf_5", "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_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "qc_adapt_illumina_novaseq_1_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": "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_methylseq_bisulfite_1_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": "Which columns should the samplesheet have for Whole-Genome Bisulfite Sequencing (WGBS / EM-seq)?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,vcf": null, "sample,cpg,methylation": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "resource_ariba_run_4", "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_low": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "noul_deprecated_dsl1_set_keyword_0", "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_sample_3_9", "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, "enum: [0, 1]": null, "format: file-path": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 0}
{"id": "subworkflow_pkg_tif_registration_stainwarpy_2", "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": {"Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow tif_registration_stainwarpy": null, "Local subworkflow TIF_REGISTRATION_STAINWARPY": null}}, "target": "Use nf-core subworkflow tif_registration_stainwarpy", "target_idx": 2}
{"id": "mod_khmer_uniquekmers_0", "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": {"khmer/uniquekmers": "In-memory nucleotide sequence k-mer counting, filtering, graph traversal and more", "mcstaging/phenoimager2mc": "Staging module for MCMICRO transforming PhenoImager .tif files into stacked and normalized ome-tif files per c", "fastk/merge": "A tool to merge FastK histograms", "openms/idfilter": "Filters peptide/protein identification results by different criteria.", "fastk/histex": "A fast K-mer counter for high-fidelity shotgun datasets"}}, "target": "khmer/uniquekmers", "target_idx": 0}
{"id": "mod_paragraph_multigrmpy_1", "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": {"biomformat_convert": "Convert biom table to different format.\nConversion between text tab-delimited, BIOM-v1 (JSON), and BIOM-v2 (HD", "bcftools_call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "paragraph_multigrmpy": "Genotype structural variants using paragraph and grmpy", "gt_stat": "GenomeTools gt-stat utility to show statistics about features contained in GFF3 files", "aardvark_merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF."}}, "target": "paragraph_multigrmpy", "target_idx": 2}
{"id": "samplesheet_arch_ont_direct_rna_se_4_2", "category": "samplesheet_schema", "state": {"assay": "Single-end Oxford Nanopore direct RNA", "first_step": "NANOPLOT"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Single fastq per sample?", "criteria": {"sample,vcf": null, "sample,fastq_1": null, "sample,fast5": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "mod_picard_positionbaseddownsamplesam_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Samples a SAM/BAM/CRAM file using flowcell position information for the best approximation of having sequenced fewer reads (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"qcat": "Demultiplexer for Nanopore samples", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "picard/positionbaseddownsamplesam": "Samples a SAM/BAM/CRAM file using flowcell position information for the best approximation of having sequenced", "custom/addmostseverepli": "Annotate a VEP annotated VCF with the most severe pLi field", "taxpasta/merge": "Standardise and merge two or more taxonomic profiles into a single table"}}, "target": "picard/positionbaseddownsamplesam", "target_idx": 2}
{"id": "samplesheet_arch_scrna_10x_v3_2_1", "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?", "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_raw2ometiff_0", "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": {"raw2ometiff": "write your description here", "deepcell/mesmer": "Deepcell/mesmer segmentation for whole-cell", "baysor/run": "Bayesian segmentation of spatial transcriptomics data.", "blast/tblastn": "Queries a BLAST DNA database", "transrate": "Reference-free and reference-based quality assessment of de novo transcriptome\nassemblies. Only sequence-based"}}, "target": "raw2ometiff", "target_idx": 0}
{"id": "intent_prepare_data_0", "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", "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": 1}
{"id": "samplesheet_arch_prealigned_bam_indexed_1_4", "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 Pre-aligned BAM variant calling pipeline?", "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": "mod_gem3_gem3mapper_0", "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": {"ariba/run": null, "varlociraptor/filterfdr": null, "vcf_filter_bcftools_ensemblvep": null, "gem3/gem3mapper": null, "bamtofastq10x": null}}, "target": "gem3/gem3mapper", "target_idx": 3}
{"id": "mod_ucsc_wigtobigwig_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert ascii format wig file to binary big wig format (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", "samtools_quickcheck": "Quickly check that input files appear to be intact. Checks that beginning of the file contains a valid header ", "hmmer_hmmlogo": "extract logo data from a profile HMM file to produce an HMM logo", "deeptools_plotpca": "Generates principal component analysis (PCA) plot using a compressed matrix generated by multibamsummary or mu", "ucsc_wigtobigwig": "Convert ascii format wig file to binary big wig format"}}, "target": "ucsc_wigtobigwig", "target_idx": 4}
{"id": "schema_std_taxprofiler_0_0", "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_id,mapped,index,file_type": null, "sample,nuclear_image,spot_table,membrane_image": null, "sample,fastq_1,fastq_2,bam,seq_type": null, "sample,fastq_1,fastq_2,fasta,run_accession": null}}, "target": "sample,fastq_1,fastq_2,fasta,run_accession", "target_idx": 3}
{"id": "samplesheet_arch_prealigned_bam_indexed_6_4", "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 are standard for Pre-aligned BAM variant calling pipeline input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null}}, "target": "sample,bam,bai", "target_idx": 1}
{"id": "noul_multiple_script_sections_invalid_18", "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_mapad_1", "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": {"csvtk_sort": "Sort  CSV (or TSV) tables", "finaletoolkit_aggbw": "Aggregates a bigWig signal over constant-length intervals\ndefined in a BED file.", "fastq_align_mapad": "Align FASTQ files against reference genome with the mapAD aDNA short-read aligner producing a sorted and index", "aardvark_merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF.", "biobambam_bamsormadup": "Parallel sorting and duplicate marking"}}, "target": "fastq_align_mapad", "target_idx": 2}
{"id": "noul_publishdir_directive_usage_2", "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_td2_longorfs_1", "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": {"finaletoolkit_fraglengthbins": "Generate a binned fragment profile and a fragment distribution histogram", "td2_longorfs": "TD2 identifies candidate coding regions within transcript sequences, such as those generated by de novo RNA-Se", "opt_stat": "stat summarizes opt binding predictions", "vcf_filter_bcftools_ensemblvep": "Filter VCF file with bcftools and filter_vep", "orfipy": "orfipy is a tool written in python/cython to extract ORFs in an extremely and fast and flexible manner."}}, "target": "td2_longorfs", "target_idx": 1}
{"id": "pipe_core10_scrnaseq_1_described", "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": {"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", "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)", "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", "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", "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": "resource_busco_download_1", "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_long": null, "process_high": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "subworkflow_pkg_fasta_clean_fcs_0", "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": {"Leave them out": null, "Local subworkflow FASTA_CLEAN_FCS": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow fasta_clean_fcs": null}}, "target": "Use nf-core subworkflow fasta_clean_fcs", "target_idx": 3}
{"id": "qc_adapt_ffpe_wes_0_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": "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": "noul_confusing_combine_with_mix_semantics_5", "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": "samplesheet_arch_prealigned_bam_indexed_0_2", "category": "samplesheet_schema", "state": {"assay": "Pre-aligned BAM variant calling pipeline", "first_step": "GATK_HAPLOTYPECALLER"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Pre-aligned BAM variant calling pipeline?", "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": "samplesheet_arch_bulk_wes_pe_3_2", "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": "Define the required samplesheet CSV header schema for Paired-end Whole Exome Sequencing (WES) target capture with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam,bai": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "field_constraint_sex_0_2", "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, "format: file-path": null, "type: boolean": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 0}
{"id": "samplesheet_arch_epigenomics_hic_6_4", "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 are standard for Hi-C chromosome conformation capture mapping input samplesheet?", "criteria": {"sample,bam": 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_pacbio_hifi_wgs_0_2", "category": "samplesheet_schema", "state": {"assay": "Long-read Pacific Biosciences HiFi sequencing", "first_step": "HIFIADAPTERFILT"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Long-read Pacific Biosciences HiFi sequencing?", "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": "qc_adapt_qc_aggregate_0_36", "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": "samplesheet_arch_spatial_visium_4_2", "category": "samplesheet_schema", "state": {"assay": "10x Visium spatial transcriptomics with histology image", "first_step": "FASTQC"}, "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,bam": null, "sample,fastq_1,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_custom_collectstats_0", "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": {"gt/stat": "GenomeTools gt-stat utility to show statistics about features contained in GFF3 files", "hamronization/fargene": "Tool to convert and summarize fARGene outputs using the hAMRonization specification", "sentieon/staralign": "Align reads to a reference genome using Sentieon STAR", "custom/collectstats": "Collects per-sample read-processing statistics (trimming, decontamination, alignment,\nfeature counting, and op", "pairtools/stats": "Calculate pairs statistics"}}, "target": "custom/collectstats", "target_idx": 3}
{"id": "resource_bcftools_call_4", "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_high": null, "process_medium": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_qc_aggregate_2_8", "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_deepvariant_rundeepvariant_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": {"deepvariant/rundeepvariant": "DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generat", "shapeit5/switch": "Program to compute switch error rate and genotyping error rate given simulated or trio data.", "bcftools/call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "gnu/sort": "Writes a sorted concatenation of file/s", "aardvark/compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF."}}, "target": "deepvariant/rundeepvariant", "target_idx": 0}
{"id": "mod_tidk_explore_1", "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": {"alignoth": "Creating alignment plots from bam files", "bam_subsampledepth_samtools": "Subsample a BAM/CRAM/SAM file using samtools to a given mean depth.\n\"region\", \"subsample_fraction\", \"mean_dept", "agat_spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "tidk_explore": "`tidk explore` attempts to find the simple telomeric repeat unit in the genome provided.\nIt will report this r", "gstama_merge": "Merge multiple transcriptomes while maintaining source information."}}, "target": "tidk_explore", "target_idx": 3}
{"id": "mod_fcsgx_cleangenome_1", "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": {"bedtools_merge": "combines overlapping or “book-ended” features in an interval file into a single feature which spans all of the", "agat_convertgff2bed": "Takes a GFF3 file and converts to a bed12 file", "abyss_abysspe": "ABySS is a de novo sequence assembler intended for short paired-end reads and genomes of all sizes.", "fastq_align_bwa": "Align reads to a reference genome using bwa then sort with samtools", "fcsgx_cleangenome": "Runs FCS-GX (Foreign Contamination Screen - Genome eXtractor) to remove foreign contamination from genome asse"}}, "target": "fcsgx_cleangenome", "target_idx": 4}
{"id": "qc_adapt_pe_illumina_fastqc_1_38", "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": "schema_std_crisprseq_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/crisprseq", "assay": "crisprseq pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/crisprseq (A pipeline for the analysis of CRISPR edited data. It allows)?", "criteria": {"sample_id,img_directory,parameter_file": null, "sample,fastq_1,fastq_2,sampleID,forwardReads": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,fastq_2,condition,reference": null}}, "target": "sample,fastq_1,fastq_2,condition,reference", "target_idx": 3}
{"id": "mod_bam_variant_demix_boot_freyja_0", "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": null, "bamclipper": null, "ascat": null, "falint": null, "ribotricer/prepareorfs": null}}, "target": "bam_variant_demix_boot_freyja", "target_idx": 0}
{"id": "qc_adapt_ont_ultra_long_1_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": "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_htodemux_1", "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": {"deepvariant_postprocessvariants": null, "demuxem": null, "htodemux": null, "multiseqdemux": null, "blat": null}}, "target": "htodemux", "target_idx": 2}
{"id": "pipe_all101_sarek_0", "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": {"pacvar": null, "viralrecon": null, "fastqrepair": null, "detaxizer": null, "sarek": null, "reportho": null, "ribomsqc": null, "circdna": null, "createpanelrefs": null, "imcyto": null}}, "target": "sarek", "target_idx": 4}
{"id": "qc_adapt_illumina_novaseq_2_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": "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_bcftools_pluginvcf2table_5", "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_high": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "qc_adapt_ont_nanoplot_0_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": "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_bulk_wes_pe_4_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": "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,bed": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_openms_fileconverter_0", "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": {"odgi/layout": "Establish 2D layouts of the graph using path-guided stochastic gradient descent. The graph must be sorted and ", "sageproteomics/sage": "sage is a search software for proteomics data", "openms/fileconverter": "Converts between different mass spectrometry file formats (e.g. mzML, mzXML, mgf, mzData, dta, dta2d, featureX", "somalier/ancestry": "Somalier can extract informative sites, evaluate relatedness, and perform quality-control on BAM/CRAM/BCF/VCF/", "mat2json": "converst matlab .mat files into json or csv files."}}, "target": "openms/fileconverter", "target_idx": 2}
{"id": "mod_epic2_epic2_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Domain calling of broad enriched genomic regions of ChIP-seq, Cut&Run or Cut&Tag (tools: epic2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amps": null, "bwa_mem": null, "umicollapse": null, "bedops_gtf2bed": null, "epic2_epic2": null}}, "target": "epic2_epic2", "target_idx": 4}
{"id": "mod_yara_index_0", "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": {"catpack/prepare": null, "yara/index": null, "centrifuge/build": null, "gatk4/genotypegvcfs": null, "merquryfk/katcomp": null}}, "target": "yara/index", "target_idx": 1}
{"id": "mod_metaphlan_metaphlan_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: metaphlan)?", "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", "bracken/bracken": "Re-estimate taxonomic abundance of metagenomic samples analyzed by kraken.", "diann": "Generic DIA-NN module for running any DIA-NN operation including in-silico library generation, preliminary ana", "metaphlan/metaphlan": "MetaPhlAn is a tool for profiling the composition of microbial communities from metagenomic shotgun sequencing", "bracken/combinebrackenoutputs": "Combine output of metagenomic samples analyzed by bracken."}}, "target": "metaphlan/metaphlan", "target_idx": 3}
{"id": "mod_mtmalign_align_0", "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": {"rattle/cluster": "Reference-free reconstruction and quantification of transcriptomes from long-read sequencing", "mtmalign/align": "Aligns protein structures using mTM-align", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "rseqc/tin": "Calculate TIN (transcript integrity number) from RNA-seq reads", "ashlar": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration"}}, "target": "mtmalign/align", "target_idx": 1}
{"id": "noul_mix_operator_async_emission_8", "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_channel_filter_operator_9", "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_viral_amplicon_artic_6_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 are standard for Viral amplicon sequencing with primers input samplesheet?", "criteria": {"sample,vcf": 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_bam_ngscheckmate_1", "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": {"gecco_convert": null, "samtools_calmd": null, "ngscheckmate_fastq": null, "ngscheckmate_patterngenerator": null, "bam_ngscheckmate": null}}, "target": "bam_ngscheckmate", "target_idx": 4}
{"id": "noul_named_output_channel_access_14", "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_phaseimpute_0", "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": {"clipseq": null, "oncoanalyser": null, "metatdenovo": null, "readsimulator": null, "denovotranscript": null, "demo": null, "lsmquant": null, "phaseimpute": null}}, "target": "phaseimpute", "target_idx": 7}
{"id": "mod_ucsc_bedtobigbed_1", "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": {"agat_convertgff2bed": "Takes a GFF3 file and converts to a bed12 file", "metaspace_converter": "Export METASPACE datasets to AnnData and SpatialData objects", "ucsc_bedtobigbed": "Convert file from bed to bigBed format", "bamtools_convert": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "lofreq_alnqual": "Lofreq subcommand to for insert base and indel alignment qualities"}}, "target": "ucsc_bedtobigbed", "target_idx": 2}
{"id": "mod_vcf2cytosure_1", "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": {"trinity": null, "panacus_visualize": null, "vg_index": null, "aardvark_merge": null, "vcf2cytosure": null}}, "target": "vcf2cytosure", "target_idx": 4}
{"id": "noul_channel_collect_operator_17", "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_dedup_stats_samtools_umicollapse_0", "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": {"Local subworkflow BAM_DEDUP_STATS_SAMTOOLS_UMICOLLAPSE": null, "Use nf-core subworkflow bam_dedup_stats_samtools_umicollapse": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Use nf-core subworkflow bam_dedup_stats_samtools_umicollapse", "target_idx": 1}
{"id": "resource_ampcombi_3", "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_single": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_spatial_visium_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/spatialaxe --input samplesheet.csv (Assay: 10x Visium spatial transcriptomics with histology image)", "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,bam": 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": "samplesheet_arch_cageseq_transcription_0_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": "Which columns should the input 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": "mod_orfipy_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: orfipy is a tool written in python/cython to extract ORFs in an extremely and fast and flexible manner. (tools: orfipy)?", "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.", "bamtools/stats": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "clippy": "Runs the Clippy CLIP peak caller", "td2/longorfs": "TD2 identifies candidate coding regions within transcript sequences, such as those generated by de novo RNA-Se", "td2/predict": "TD2 identifies candidate coding regions within transcript sequences, such as those generated by de novo RNA-Se"}}, "target": "orfipy", "target_idx": 0}
{"id": "mod_controlfreec_freec2circos_0", "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": {"controlfreec/freec2bed": "Plot Freec output", "pigz/compress": "Compresses files with pigz.", "cnvnator/cnvnator": "CNVnator is a command line tool for CNV/CNA analysis from depth-of-coverage by mapped reads.", "controlfreec/freec2circos": "Format Freec output to circos input format", "goatools/findenrichment": "Find enriched GO terms in a list of genes"}}, "target": "controlfreec/freec2circos", "target_idx": 3}
{"id": "mod_fastq_shortreads_preprocess_qc_0", "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": {"xeniumranger/resegment": null, "ariba/getref": null, "adapterremovalfixprefix": null, "fastq_shortreads_preprocess_qc": null, "trtools/dumpstr": null}}, "target": "fastq_shortreads_preprocess_qc", "target_idx": 3}
{"id": "noul_dynamic_resource_allocation_4", "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": "samplesheet_arch_ont_demux_barcodes_3_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": "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,barcode": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 2}
{"id": "mod_metaphlan3_mergemetaphlantables_1", "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": {"tinc": null, "dedup": null, "metaphlan3_mergemetaphlantables": null, "argnorm": null, "binette": null}}, "target": "metaphlan3_mergemetaphlantables", "target_idx": 2}
{"id": "qc_adapt_ont_nanoplot_0_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": "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_purgedups_getseqs_1", "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_getseqs": null, "president": null, "rpbp_extractmetageneprofiles": null, "phyloflash": null, "purgedups_purgedups": null}}, "target": "purgedups_getseqs", "target_idx": 0}
{"id": "resource_annotsv_annotsv_5", "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_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_hostile_clean_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Removes host reads from short- and long-read FASTQ sequencing files (tools: hostile)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vsearch/cluster": null, "gridss/extractoverlappingfragments": null, "hostile/clean": null, "hostile/fetch": null, "deacon/index": null}}, "target": "hostile/clean", "target_idx": 2}
{"id": "samplesheet_arch_dual_rnaseq_host_pathogen_5_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": "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": 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": "field_constraint_fastq_2_3_11", "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, "pattern: ^\\S+\\.bam$": null, "enum: [0, 1]": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 1}
{"id": "qc_adapt_ffpe_wes_0_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": "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_bio2zarr_vcf2zarrexplode_3", "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_long": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_gubbins_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Gubbins (Genealogies Unbiased By recomBinations In Nucleotide Sequences) is an algorithm that iteratively identifies loci containing elevated densities of base substitutions while concurrently constructing a phylogeny based on the putative point mutations outside of these regions. (tools: gubbins)?", "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.", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "gzrt": "gzrecover is a program that will attempt to extract any readable data out of a gzip file that has been corrupt", "ashlar": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration", "gubbins": "Gubbins (Genealogies Unbiased By recomBinations In Nucleotide Sequences) is an algorithm that iteratively iden"}}, "target": "gubbins", "target_idx": 4}
{"id": "samplesheet_arch_viral_ont_single_6_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 are standard for Viral genome sequencing on Oxford Nanopore MinION / GridION input samplesheet?", "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": "mod_fgumi_merge_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge pre-sorted BAM files into a single sorted BAM (tools: fgumi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgumi_merge": "Merge pre-sorted BAM files into a single sorted BAM", "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", "skani_search": "Memory-efficient ANI database queries with skani.", "htsnimtools_vcfcheck": "This tools takes a background VCF, such as gnomad, that has full genome (though in some cases, users will inst"}}, "target": "fgumi_merge", "target_idx": 0}
{"id": "resource_atlas_recal_0", "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_low": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_picard_collectwgsmetrics_1", "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": {"samtools_collate": null, "angsd_dosaf": null, "abra2": null, "picard_collectwgsmetrics": null, "alignoth": null}}, "target": "picard_collectwgsmetrics", "target_idx": 3}
{"id": "mod_plastid_makewiggle_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create wiggle or bedGraph files from alignment files after applying a read mapping rule (e.g. to map ribosome-protected footprints at their P-sites), for visualization in a genome browser (tools: plastid)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"svim/alignment": "Structural variant detection from long-read sequencing alignments using SVIM.", "agat/spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "savana/to": "Tumour-only somatic SV calling with optional copy-number analysis in SAVANA", "alignoth": "Creating alignment plots from bam files", "plastid/makewiggle": "Create wiggle or bedGraph files from alignment files after applying a read mapping rule (e.g. to map ribosome-"}}, "target": "plastid/makewiggle", "target_idx": 4}
{"id": "mod_estsfs_0", "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": {"purgedups/histplot": null, "tidk/search": null, "estsfs": null, "angsd/realsfs": null, "arriba/arriba": null}}, "target": "estsfs", "target_idx": 2}
{"id": "samplesheet_arch_smartseq_plate_based_4_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": "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,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_prealigned_bam_indexed_7_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": "Which columns should the samplesheet have for BAM inputs?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,vcf": null, "sample,bam,bai": null}}, "target": "sample,bam,bai", "target_idx": 3}
{"id": "qc_adapt_illumina_novaseq_1_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": "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": "schema_std_variantbenchmarking_2_0", "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": {"RNA_ID,RNA_BAM_FILE,RNA_BAI_FILE,DNA_ID,DNA_VCF_FILE": null, "id,test_vcf,test_regions,caller,subsample": null, "id,fasta,sequence": null, "sample,bam,vcf,rna_matrix,hto_matrix": null}}, "target": "id,test_vcf,test_regions,caller,subsample", "target_idx": 1}
{"id": "mod_fq_subsample_0", "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": {"art/illumina": null, "catpack/contigs": null, "parabricks/deepvariant": null, "fq/subsample": null, "ariba/getref": null}}, "target": "fq/subsample", "target_idx": 3}
{"id": "qc_adapt_ont_nanoplot_0_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": "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": "noul_workflow_completion_lifecycle_hook_20", "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_bam_markduplicates_samtools_0", "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": {"iphop/predict": "Predict phage host using iPHoP", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "ascat": "copy number profiles of tumour cells.", "cowpy": "Print any text in a cow or other characters", "bam_markduplicates_samtools": "Samtools markduplicate SAM/BAM/CRAM file"}}, "target": "bam_markduplicates_samtools", "target_idx": 4}
{"id": "resource_bigslice_bigslice_1", "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_long": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_metatranscriptome_denovo_6_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 are standard for Environmental community metatranscriptomics de novo assembly input samplesheet?", "criteria": {"sample,bam": 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": "samplesheet_arch_cfdna_liquid_biopsy_3_3", "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": "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, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "patient,sample,timepoint,volume_ml,fastq_1,fastq_2", "target_idx": 1}
{"id": "samplesheet_arch_pediatric_trio_somatic_1_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": "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,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": "samplesheet_arch_cutandrun_pe_5_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": "In Nextflow pipeline nf-core/cutandrun, determine the input samplesheet column structure for: CUT&RUN / CUT&TAG chromatin profiling with IgG control.", "criteria": {"sample,fastq_1,fastq_2,target,control": null, "sample,fastq_1,fastq_2": null, "sample,spikein,fastq": null, "sample,target,control": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 0}
{"id": "mod_ucsc_wigtobigwig_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert ascii format wig file to binary big wig format (tools: ucsc)?", "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", "ctatsplicing/startocancerintrons": "Detection and annotation of aberrant splicing isoforms in cancer transcriptomes", "ucsc/wigtobigwig": "Convert ascii format wig file to binary big wig format", "deeptools/bamcompare": "Compares two BAM files based on the number of mapped reads and generates a bigWig or bedGraph file with the lo", "deeptools/multibigwigsummary": "Computes the average scores for each of the files in every genomic region"}}, "target": "ucsc/wigtobigwig", "target_idx": 2}
{"id": "samplesheet_arch_prealigned_bam_indexed_6_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 are standard for Pre-aligned BAM variant calling pipeline input samplesheet?", "criteria": {"sample,bam": null, "sample,vcf": null, "sample,bam,bai": null, "sample,fastq_1": null}}, "target": "sample,bam,bai", "target_idx": 2}
{"id": "mod_sentieon_dnascope_1", "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": "DNAscope algorithm performs an improved version of Haplotype variant calling.", "sentieon_collectvcmetrics": "Accelerated implementation of the Picard CollectVariantCallingMetrics tool.", "tiff_segmentation_vpt": "Perform segmentation of MERSCOPE TIFF images using the vizgen-postprocessing tool", "sentieon_coveragemetrics": "Accelerated implementation of the GATK DepthOfCoverage tool.", "paraphase": "HiFi-based caller for highly homologous genes"}}, "target": "sentieon_dnascope", "target_idx": 0}
{"id": "samplesheet_arch_cancer_somatic_bam_2_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 should the input samplesheet have?", "criteria": {"sample,bam,bai": null, "patient,sample,status,bam,bai": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,vcf": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_0_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": "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_mirtop_counts_0", "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": {"bcftools/concat": "Concatenate VCF files", "agat/spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "mirtop/stats": "mirtop gff gets the number of isomiRs and miRNAs annotated in the GFF file by isomiR category.", "mirtop/counts": "mirtop counts generates a file with the minimal information about each sequence and the count data in columns ", "nacho/normalize": "NACHO (NAnostring quality Control dasHbOard) is developed for NanoString nCounter data.\nNanoString nCounter da"}}, "target": "mirtop/counts", "target_idx": 3}
{"id": "samplesheet_arch_rnafusion_pe_2_2", "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 input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,fastq_2": null, "sample,fusion_bed": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 0}
{"id": "noul_channel_factory_inside_process_body_13", "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_msisensorpro_msisomatic_1", "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": {"ferrohgvs_parse": null, "msisensorpro_msisomatic": null, "msisensorpro_pro": null, "glimpse2_phase": null, "msisensor2_msi": null}}, "target": "msisensorpro_msisomatic", "target_idx": 1}
{"id": "mod_bedtools_multiinter_0", "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": {"deacon/filter": "Filter DNA sequences using index of reference genome", "bedtools/genomecov": "Computes histograms (default), per-base reports (-d) and BEDGRAPH (-bg) summaries of feature coverage (e.g., a", "bedtools/complement": "Returns all intervals in a genome that are not covered by at least one interval in the input BED/GFF/VCF file.", "bedtools/multiinter": "Identifies common intervals among multiple (and subsets thereof) sorted BED/GFF/VCF files.", "picard/meanqualitybycycle": "Collect metrics about the mean quality by cycle of a paired-end library."}}, "target": "bedtools/multiinter", "target_idx": 3}
{"id": "resource_atlas_splitmerge_5", "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_single": null, "process_long": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "intent_ask_question_18", "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", "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"}}, "target": "ask_question", "target_idx": 2}
{"id": "mod_msisensorpro_scan_1", "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_msisomatic": "MSIsensor-pro evaluates Microsatellite Instability (MSI) for cancer patients with next generation sequencing d", "merqury_hapmers": "A script to generate hap-mer dbs for trios", "arcashla_extract": "Extracts reads mapped to chromosome 6 and any HLA decoys or chromosome 6 alternates.", "msisensorpro_baseline": "MSIsensor-pro/baseline builds a baseline microsatellite file from a panel of normal samples, for use with msis", "msisensorpro_scan": "MSIsensor-pro evaluates Microsatellite Instability (MSI) for cancer patients with next generation sequencing d"}}, "target": "msisensorpro_scan", "target_idx": 4}
{"id": "noul_container_environment_specification_21", "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_0_6", "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_ffpe_wes_0_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": "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_fastq_find_mirna_mirdeep2_2", "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, "Keep the modules in the main workflow": null, "Local subworkflow FASTQ_FIND_MIRNA_MIRDEEP2": null, "Use nf-core subworkflow fastq_find_mirna_mirdeep2": null}}, "target": "Use nf-core subworkflow fastq_find_mirna_mirdeep2", "target_idx": 3}
{"id": "schema_std_funcprofiler_2_1", "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": {"id,test_vcf,test_regions,caller,subsample": null, "sample,fastq_1,fastq_2,fastq_barcode,expected_cells": null, "sample,fastq_1,fastq_2,fasta,run_accession": null, "sample,bundle,image": null}}, "target": "sample,fastq_1,fastq_2,fasta,run_accession", "target_idx": 2}
{"id": "mod_fgumi_duplex_0", "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": {"chelae/trim": null, "merquryfk/hapmaker": null, "flash": null, "fgbio/groupreadsbyumi": null, "fgumi/duplex": null}}, "target": "fgumi/duplex", "target_idx": 4}
{"id": "resource_bioawk_3", "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_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_bedtools_subtract_5", "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_long": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "field_constraint_fastq_2_0_13", "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, "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": "resource_annosine_3", "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_low": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_ffpe_wes_2_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": "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_vcf_annotation_pipeline_3_1", "category": "samplesheet_schema", "state": {"assay": "Downstream functional annotation of pre-called VCF files", "first_step": "ENSEMBLVEP", "template": "nf-core/raredisease"}, "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,bed": null, "sample,vcf": null, "sample,vcf,tbi": null}}, "target": "sample,vcf,tbi", "target_idx": 3}
{"id": "mod_gatk4_createsequencedictionary_0", "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": {"amrfinderplus/run": "Identify antimicrobial resistance in gene or protein sequences", "gatk4/createsequencedictionary": "Creates a sequence dictionary for a reference sequence", "agrvate": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants", "gatk4/annotateintervals": "Annotates intervals with GC content, mappability, and segmental-duplication content", "fgbio/callmolecularconsensusreads": "Calls consensus sequences from reads with the same unique molecular tag."}}, "target": "gatk4/createsequencedictionary", "target_idx": 1}
{"id": "subworkflow_pkg_h5ad_removebackground_barcodes_cellbender_anndata_1", "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, "Local subworkflow H5AD_REMOVEBACKGROUND_BARCODES_CELLBENDER_ANNDATA": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow h5ad_removebackground_barcodes_cellbender_anndata", "target_idx": 0}
{"id": "samplesheet_arch_prealigned_cram_indexed_5_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": "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,cram,crai": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,cram,crai", "target_idx": 1}
{"id": "schema_std_lsmquant_2_1", "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": {"id,raw_file": null, "seeds,network,perturbed_networks": null, "sample_id,img_directory,parameter_file": null, "sample,fastq_1,fastq_2,vcf": null}}, "target": "sample_id,img_directory,parameter_file", "target_idx": 2}
{"id": "mod_gstama_collapse_0", "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": {"gstama/collapse": "Collapse redundant transcript models in Iso-Seq data.", "glimpse/chunk": "Defines chunks where to run imputation", "isoseq3/tag": "Extract UMI and cell barcodes", "gstama/merge": "Merge multiple transcriptomes while maintaining source information.", "maxquant/lfq": "Run standard proteomics data analysis with MaxQuant, mostly dedicated to label-free. Paths to fasta and raw fi"}}, "target": "gstama/collapse", "target_idx": 0}
{"id": "pipe_all101_reportho_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: 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": {"scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "references": "nf-core/references is a bioinformatics pipeline that build references, for multiple use cases [genome, references, repro", "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", "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", "lsmquant": "A pipeline for processing and analysis of light-sheet microscopy images. [3dunet, image-analysis, image-processing]", "isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a", "reportho": "nf-core pipeline for comparative analysis of ortholog predictions [ortholog]", "drugresponseeval": "Pipeline for testing drug response prediction models in a statistically and biologically sound way. [cell-lines, cross-v"}}, "target": "reportho", "target_idx": 8}
{"id": "mod_ragtag_scaffold_1", "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": {"abacas": "Contiguate draft genome assembly", "nanoplot": "Run NanoPlot on nanopore-sequenced reads", "ragtag_scaffold": "Scaffolding is the process of ordering and orienting draft assembly (query)\nsequences into longer sequences. G", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "rasusa": "Randomly subsample sequencing reads to a specified coverage"}}, "target": "ragtag_scaffold", "target_idx": 2}
{"id": "samplesheet_arch_rare_disease_trio_2_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 should the input samplesheet have?", "criteria": {"sample,bam,bai": 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": "resource_bbmap_bbmerge_1", "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_low": null, "process_long": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_singlecell_parse_splitseq_0_4", "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 for: Parse Biosciences Split-seq combinatorial barcoding?", "criteria": {"sample,fastq_1": null, "sample,well,plate": null, "sample,subpool,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,subpool,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_seqfu_check_0", "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": {"hificnv": null, "samtools/quickcheck": null, "hmmcopy/readcounter": null, "seqfu/stats": null, "seqfu/check": null}}, "target": "seqfu/check", "target_idx": 4}
{"id": "mod_deacon_indexunion_0", "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": {"deacon/indexunion": "Combine multiple deacon indexes (A ∪ B ...)", "fastq_subsample_fq_salmon": "Subsample fastq", "biscuit/qc": "Perform basic quality control on a BAM file generated with Biscuit", "cadd": "CADD is a tool for scoring the deleteriousness of single nucleotide variants as well as insertion/deletions va", "bcftools/index": "Index VCF tools"}}, "target": "deacon/indexunion", "target_idx": 0}
{"id": "mod_genotyphi_parse_1", "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", "arcashla_extract": "Extracts reads mapped to chromosome 6 and any HLA decoys or chromosome 6 alternates.", "samtools_faidx": "Index FASTA file, and optionally generate a file of chromosome sizes", "gfatools_stat": "Summary statistics for GFA files", "quilt_quilt": "QUILT is an R and C++ program for rapid genotype imputation from low-coverage sequence using a large reference"}}, "target": "genotyphi_parse", "target_idx": 0}
{"id": "mod_viennarna_rnalfold_0", "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": {"ctatsplicing/startocancerintrons": null, "fusioncatcher/build": null, "viennarna/rnalfold": null, "fasta_consensus_autocycler": null, "odgi/sort": null}}, "target": "viennarna/rnalfold", "target_idx": 2}
{"id": "mod_repeatmasker_repeatmasker_0", "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": {"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", "gatk4/mutect2": "Call somatic SNVs and indels via local assembly of haplotypes.", "repeatmasker/repeatmasker": "Screening DNA sequences for interspersed repeats and low complexity DNA sequences", "gappa/examineheattree": "colours a phylogeny with placement densities"}}, "target": "repeatmasker/repeatmasker", "target_idx": 3}
{"id": "mod_cooltools_eigscis_0", "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": {"cooltools/eigscis": "Perform eigen value decomposition on a cooler matrix to calculate compartment signal by finding the eigenvecto", "chromap/chromap": "Performs preprocessing and alignment of chromatin fastq files to fasta reference files using chromap.", "catpack/contigs": "Taxonomic classification of long DNA sequences and metagenome assembled genomes (e.g. contigs, MAGs / bins).", "calder2": "Hierarchical Hi-C compartment computation", "ragtag/scaffold": "Scaffolding is the process of ordering and orienting draft assembly (query)\nsequences into longer sequences. G"}}, "target": "cooltools/eigscis", "target_idx": 0}
{"id": "mod_amulety_antiberta2_1", "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_embed": null, "amulety_esm2": null, "cellrangerarc_mkref": null, "amulety_antiberta2": null, "openms_decoydatabase": null}}, "target": "amulety_antiberta2", "target_idx": 3}
{"id": "qc_adapt_ffpe_wes_2_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": "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": "qc_adapt_illumina_novaseq_1_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": "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_ribodetector_0", "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": {"fusioncatcher/build": "Build references for fusioncatcher", "ribodetector": "Accurate and rapid RiboRNA sequences Detector based on deep learning", "foldcomp/decompress": "Decompression tool for foldcomp compressed structures", "circexplorer2/annotate": "Annotate circRNAs detected in the output from CIRCexplorer2 parse", "popscle/dscpileup": "Software to pileup reads and corresponding base quality for each overlapping SNPs and each barcode."}}, "target": "ribodetector", "target_idx": 1}
{"id": "mod_ismapper_0", "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": {"ismapper": "Identify insertion sites positions in bacterial genomes", "cadd": "CADD is a tool for scoring the deleteriousness of single nucleotide variants as well as insertion/deletions va", "cutesv": "structural-variant calling with cutesv", "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"}}, "target": "ismapper", "target_idx": 0}
{"id": "schema_std_funcprofiler_1_1", "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,fastq_1,fastq_2,bam,seq_type": null, "sample,type,level,msfile": null, "condition,type,microbiome_path,alleles,weights_path": null, "sample,fastq_1,fastq_2,fasta,run_accession": null}}, "target": "sample,fastq_1,fastq_2,fasta,run_accession", "target_idx": 3}
{"id": "subworkflow_pkg_fastq_align_hisat2_2", "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, "Use nf-core subworkflow fastq_align_hisat2": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fastq_align_hisat2", "target_idx": 1}
{"id": "local_subworkflow_checkirma_0_5", "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": "mod_gatk4_analyzecovariates_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Evaluate and compare base quality score recalibration (BQSR) tables (tools: gatk4)?", "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", "gatk4/analyzecovariates": "Evaluate and compare base quality score recalibration (BQSR) tables", "bam_variant_calling_sort_freebayes_bcftools": "Call variants using freebayes, then sort and index", "parabricks/applybqsr": "NVIDIA Clara Parabricks GPU-accelerated apply Base Quality Score Recalibration (BQSR).", "gatk4spark/applybqsr": "Apply base quality score recalibration (BQSR) to a bam file"}}, "target": "gatk4/analyzecovariates", "target_idx": 1}
{"id": "qc_adapt_ont_nanoplot_2_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": "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_bwafastalign_mem_2", "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_low": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_high", "target_idx": 3}
{"id": "local_subworkflow_variantsofint_2_4", "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, "Use nf-core subworkflow variantsofint": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Local subworkflow VARIANTSOFINT", "target_idx": 0}
{"id": "intent_prepare_data_8", "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", "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": "prepare_data", "target_idx": 3}
{"id": "pipe_all101_isoseq_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: 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": {"longraredisease": "Long read sequencing pipeline to identify variants in patients with neurodevelopmental disorders  [nanopore, pacbio]", "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]", "variantbenchmarking": "Pipeline to evaluate and validate the accuracy of variant calling methods in genomic research [benchmark, small-variants", "isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a"}}, "target": "isoseq", "target_idx": 4}
{"id": "resource_bamreadcount_2", "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_single": null, "process_low": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_bedtools_shuffle_2", "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_high": null, "process_single": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_controlfreec_makegraph_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": {"controlfreec/freec2bed": null, "seqkit/rmdup": null, "cnvpytor/importreaddepth": null, "controlfreec/makegraph": null, "h5ad_removebackground_barcodes_cellbender_anndata": null}}, "target": "controlfreec/makegraph", "target_idx": 3}
{"id": "qc_adapt_illumina_novaseq_2_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": "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_spatial_visium_3_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": "Define the required samplesheet CSV header schema for 10x Visium spatial transcriptomics with histology image with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,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": "mod_tcoffee_alncompare_0", "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": {"gt/stat": "GenomeTools gt-stat utility to show statistics about features contained in GFF3 files", "busco/phylogenomics": "Construct species phylogenies using BUSCO proteins", "samtools/calmd": "calculates MD and NM tags", "tcoffee/alncompare": "Compares 2 alternative MSAs to evaluate them.", "alignoth": "Creating alignment plots from bam files"}}, "target": "tcoffee/alncompare", "target_idx": 3}
{"id": "mod_elprep_filter_1", "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": {"fastqe": "fastqe is a bioinformatics command line tool that uses emojis to represent and analyze genomic data.", "biobambam_bamsormadup": "Parallel sorting and duplicate marking", "elprep_filter": "Filter, sort and markdup sam/bam files, with optional BQSR and variant calling.", "custom_multiqccustombiotype": "Generate MultiQC-compatible biotype count summaries from featureCounts output", "duphold": "SV callers like lumpy look at split-reads and pair distances to find structural variants. This tool is a fast "}}, "target": "elprep_filter", "target_idx": 2}
{"id": "mod_rseqc_junctionannotation_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": {"sequenzautils_bam2seqz": "Sequenza-utils bam2seqz process BAM and Wiggle files to produce a seqz file", "hisat2_extractsplicesites": "Extracts splicing sites from a gtf files", "custom_bed12codonpositions": "Expand a BED12 into a BED6 of in-frame mRNA positions, projected back\nto genomic coordinates. Default behaviou", "rseqc_junctionannotation": "compare detected splice junctions to reference gene model", "custom_orfnormalise": "Convert one ORF caller's per-sample output table into a unified BED12 plus a\nsidecar metadata TSV, ready for c"}}, "target": "rseqc_junctionannotation", "target_idx": 3}
{"id": "mod_gcta_grmcutoff_0", "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/bivariateremlldms": "Run bivariate REML-LDMS analysis with an MGRM manifest", "gcta/adjustgrm": "Adjust a dense GRM for incomplete tagging using `gcta --grm-adj`", "goleft/indexsplit": "Quickly generate evenly sized (by amount of data) regions across a number of bam/cram files", "trgt/plot": "Visualize tandem repeats genotyped by TRGT", "gcta/grmcutoff": "Apply a genetic relationship cutoff to a dense GRM using `gcta --grm-cutoff`"}}, "target": "gcta/grmcutoff", "target_idx": 4}
{"id": "samplesheet_arch_bulk_small_rna_4_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": "What samplesheet columns are expected when inputs are: Single-end 50bp miRNA reads with 3-prime adapter?", "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": "qc_adapt_targeted_amplicon_1_8", "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_cutandrun_pe_3_5", "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": "Define the required samplesheet CSV header schema for CUT&RUN / CUT&TAG chromatin profiling with IgG control with entry step FASTQC.", "criteria": {"sample,spikein,fastq": 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_nacho_normalize_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": {"cnvnator/convert2vcf": "convert2vcf.pl is command line tool to convert CNVnator calls to vcf format.", "samtools/sort": "Sort SAM/BAM/CRAM file", "nacho/normalize": "NACHO (NAnostring quality Control dasHbOard) is developed for NanoString nCounter data.\nNanoString nCounter da", "nacho/qc": "NACHO (NAnostring quality Control dasHbOard) is developed for NanoString nCounter data.\nNanoString nCounter da", "mirtop/export": "mirtop export generates files such as fasta, vcf or compatible with isomiRs bioconductor package"}}, "target": "nacho/normalize", "target_idx": 2}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_0_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": "Which columns should the input samplesheet have for: Hybrid bacterial assembly combining short Illumina and long Nanopore reads?", "criteria": {"sample,fasta": null, "sample,bam": 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_spatial_visium_1_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": "Which columns should the samplesheet have for 10x Visium spatial transcriptomics with histology image?", "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_plink_bmerge_1", "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": {"plink_exclude": null, "trycycler_cluster": null, "plink_indeppairwise": null, "parabricks_rnafq2bam": null, "plink_bmerge": null}}, "target": "plink_bmerge", "target_idx": 4}
{"id": "mod_lofreq_viterbi_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": {"pasty": null, "picard/createsequencedictionary": null, "bcftools/concat": null, "bcftools/call": null, "lofreq/viterbi": null}}, "target": "lofreq/viterbi", "target_idx": 4}
{"id": "mod_wisecondorx_gender_1", "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": {"savana_to": null, "wisecondorx_gender": null, "biscuit_epiread": null, "kraken2_build": null, "wisecondorx_newref": null}}, "target": "wisecondorx_gender", "target_idx": 1}
{"id": "qc_adapt_bulk_multiqc_2_5", "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": "samplesheet_arch_pacbio_hifi_wgs_2_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 should the input samplesheet have?", "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": "resource_bbmap_bbduk_3", "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_long": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_annosine_1", "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_spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "annosine": "Accelerating de novo SINE annotation in plant and animal genomes", "emboss_revseq": "the revseq program from emboss reverse complements a nucleotide sequence", "regenie_runl0": "Run one REGENIE step 1 level-0 job from a split master file", "agat_spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated"}}, "target": "annosine", "target_idx": 1}
{"id": "mod_cellranger_mkvdjref_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to build the VDJ reference needed by the 10x Genomics Cell Ranger tool. Uses the cellranger mkvdjref command. (tools: cellranger)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"krakenuniq/build": "Download and build (custom) KrakenUniq databases", "cellranger/mkvdjref": "Module to build the VDJ reference needed by the 10x Genomics Cell Ranger tool. Uses the cellranger mkvdjref co", "arriba/download": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data.", "survivor/bedpetovcf": "Converts a bedpe file to a VCF file (beta version)", "bbmap/bbsplit": "Split sequencing reads by mapping them to multiple references simultaneously"}}, "target": "cellranger/mkvdjref", "target_idx": 1}
{"id": "schema_std_genomeassembler_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/genomeassembler", "assay": "genomeassembler pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/genomeassembler (Assembly and scaffolding of haploid / unphased genomes from )?", "criteria": {"sample,group,ref_fasta,ref_gff,use_ref": null, "condition,type,microbiome_path,alleles,weights_path": null, "sample,bam,vcf,rna_matrix,hto_matrix": null, "sample,fastq_1,fastq_2,antibody,control": null}}, "target": "sample,group,ref_fasta,ref_gff,use_ref", "target_idx": 0}
{"id": "mod_panacus_histgrowth_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculates a coverage histogram from a GFA file and constructs a growth table from this as either a TSV or HTML file (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", "mash/sketch": "Creates vastly reduced representations of sequences using MinHash", "eautils/fastqstats": "Calculate general and per-base statistics from FASTQ files", "panacus/histgrowth": "Calculates a coverage histogram from a GFA file and constructs a growth table from this as either a TSV or HTM", "bcftools/roh": "A program for detecting runs of homo/autozygosity. Only bi-allelic sites are considered."}}, "target": "panacus/histgrowth", "target_idx": 3}
{"id": "samplesheet_arch_bulk_small_rna_2_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 should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,mirna_id": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "mod_fastq_align_bamcmp_bwa_1", "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": {"bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files.", "fastq_align_bamcmp_bwa": "Align reads to two different reference genomes using bwa, then use bamcmp to keep only reads that align better", "gatk4_modelsegments": "Converts copy number ratios (and optonally allelic counts) to copy number segments", "spotiflow": "Spotiflow, accurate and efficient spot detection with stereographic flow.", "atlas_pmd": "Estimate the post-mortem damage patterns of DNA"}}, "target": "fastq_align_bamcmp_bwa", "target_idx": 1}
{"id": "mod_bcftools_concat_0", "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": {"aardvark/merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF.", "bcftools/concat": "Concatenate VCF files", "csvtk/join": "Join two or more CSV (or TSV) tables by selected fields into a single table", "bcftools/rohviz": "Visualise the output of bcftools roh", "bcftools/filter": "Filters VCF files"}}, "target": "bcftools/concat", "target_idx": 1}
{"id": "samplesheet_arch_bulk_wgs_pe_0_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": "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": null, "sample,fastq_1,fastq_2,group": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "samplesheet_arch_ampliseq_its_fungal_4_2", "category": "samplesheet_schema", "state": {"assay": "Fungal ITS1/ITS2 marker gene amplicon surveillance", "first_step": "FASTQC"}, "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,fastq_1": null, "sample,unite_fasta": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "pipe_all101_atacseq_5", "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": {"methylseq": "Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair [bisulfi", "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, ", "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": "atacseq", "target_idx": 3}
{"id": "samplesheet_arch_chipseq_with_control_7_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": "Which columns should the samplesheet have for ChIP-seq with controls?", "criteria": {"sample,fastq_1": null, "sample,antibody,control": null, "sample,fastq_1,fastq_2,antibody,control": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 2}
{"id": "mod_muse_sump_1", "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": {"mudskipper_bulk": "Convert genomic BAM/SAM files to transcriptomic BAM/RAD files.", "bam_variant_demix_boot_freyja": "Recover relative lineage abundances from mixed SARS-CoV-2 samples from a sequencing dataset (BAM aligned to th", "bcftools_call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "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."}}, "target": "muse_sump", "target_idx": 3}
{"id": "mod_apbs_0", "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": {"pdb2pqr": "Convert PDB files to PQR format by\nassigning charge and radius parameters for\nelectrostatics calculations (e.g", "bacphlip": "A bacteriophage lifestyle prediction tool", "vcontact3/prepareddatabases": "Prepare and format databases for vCONTACT3 viral taxonomic analysis", "apbs": "Compute biomolecular electrostatics by solving the Poisson-Boltzmann equation\nusing APBS (Adaptive Poisson-Bol", "gemmi/cif2json": "Convert macromolecular structure files from mmCIF format to JSON format using gemmi."}}, "target": "apbs", "target_idx": 3}
{"id": "pipe_all101_variantbenchmarking_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: 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": {"variantbenchmarking": null, "molkart": null, "raredisease": null, "viralrecon": null, "ribomsqc": null, "circdna": null, "viralmetagenome": null, "createpanelrefs": null}}, "target": "variantbenchmarking", "target_idx": 0}
{"id": "qc_adapt_ffpe_wes_0_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": "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": "noul_default_empty_channel_behavior_0", "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_proteomics_dia_4_2", "category": "samplesheet_schema", "state": {"assay": "Data-Independent Acquisition (DIA) quantitative mass spectrometry", "first_step": "INPUT_CHECK"}, "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,mzml": null, "sample,peptides_tsv": null, "sample,raw_file,condition": null}}, "target": "sample,raw_file,condition", "target_idx": 3}
{"id": "samplesheet_arch_cancer_tumor_only_6_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 are standard for Tumor-only somatic variant calling without matched normal input samplesheet?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1": null, "patient,normal,tumor": null, "sample,bam": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 0}
{"id": "noul_container_environment_specification_0", "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_singlecell_multiqc_0_20", "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_cancer_longitudinal_1_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": "Which columns should the samplesheet have for Longitudinal cancer monitoring across multiple timepoints?", "criteria": {"patient,sample,status,fastq_1,fastq_2": 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": "core_tool_deepvariant_described_2", "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", "deepvariant": "Deep learning-based variant caller that calls genetic variants using neural networks", "varscan2": "Variant caller", "freebayes": "Bayesian caller", "clair3": "Neural caller"}}, "target": "deepvariant", "target_idx": 1}
{"id": "mod_vuegen_0", "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": {"pcangsd/inbreeding": "Estimate per-sample inbreeding coefficients from genotype likelihoods", "vuegen": "The VueGen nf-core module is designed to automate report generation from outputs produced by other modules, su", "emboss/cons": "cons calculates a consensus sequence from a multiple sequence alignment. To obtain the consensus, the sequence", "rmarkdownnotebook": "Render an rmarkdown notebook. Supports parametrization.", "jupyternotebook": "Render jupyter (or jupytext) notebooks to HTML reports. Supports parametrization\nthrough papermill."}}, "target": "vuegen", "target_idx": 1}
{"id": "field_constraint_phenotype_3_0", "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: [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_bedtools_unionbedg_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Combines multiple BedGraph files into a single file (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.", "bam_qc_picard": "Produces comprehensive statistics from BAM file", "bedtools/unionbedg": "Combines multiple BedGraph files into a single file", "agat/convertbed2gff": "Takes a bed12 file and converts to a GFF3 file", "dastool/fastatocontig2bin": "Helper script to convert a set of bins in fasta format to tabular scaffolds2bin format"}}, "target": "bedtools/unionbedg", "target_idx": 2}
{"id": "samplesheet_arch_mira_influenza_sc2_0_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": "Which columns should the input samplesheet have for: Custom MIRA-NF Influenza / SC2 pipeline?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,fastq_1,fastq_2,group": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_singlem_dbdownload_0", "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": {"regenie/step2": null, "singlem/dbdownload": null, "amps": null, "biomformat/convert": null, "ribocode/metaplots": null}}, "target": "singlem/dbdownload", "target_idx": 1}
{"id": "pipe_all101_longraredisease_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for nanopore. Best pipeline:", "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]", "longraredisease": "Long read sequencing pipeline to identify variants in patients with neurodevelopmental disorders  [nanopore, pacbio]", "molkart": "A pipeline for processing Molecular Cartography data from Resolve Bioscience (combinatorial FISH) [fish, image-processin", "magmap": "Best-practice analysis pipeline for mapping reads to a (large) collections of genomes", "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]", "sopa": "Nextflow version of Sopa - spatial omics pipeline and analysis [segmentation, spatial-omics, spatial-proteomics]", "metapep": "From metagenomes to epitopes and beyond", "smrnaseq": "A small-RNA sequencing analysis pipeline [small-rna, smrna-seq]", "rnastructurome": "a bioinformatics pipeline for analysing chemical high-throughput RNA structure-probing data [dms, map, rna-structure]"}}, "target": "longraredisease", "target_idx": 1}
{"id": "mod_agat_convertbed2gff_0", "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": {"agat/convertbed2gff": null, "maxquant/lfq": null, "agat/convertspgff2tsv": null, "amrfinderplus/run": null, "abacas": null}}, "target": "agat/convertbed2gff", "target_idx": 0}
{"id": "pipe_all101_demultiplex_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Demultiplexing pipeline for sequencing data. Topics: bases2fastq, bcl2fastq, demultiplexing, elementbiosciences, illumina. ?", "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", "metaboigniter": "Pre-processing of mass spectrometry-based metabolomics data with quantification and identification based on MS1 and MS2 ", "nanoseq": "Nanopore demultiplexing, QC and alignment pipeline [alignment, demultiplexing, nanopore]", "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]", "demultiplex": "Demultiplexing pipeline for sequencing data [bases2fastq, bcl2fastq, demultiplexing]", "nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]", "viralintegration": "Analysis pipeline for the identification of viral integration events in genomes using a chimeric read approach. [chimeri", "circdna": "Pipeline for the identification of extrachromosomal circular DNA (ecDNA) from Circle-seq, WGS, and ATAC-seq data that we", "readsimulator": "A pipeline to simulate sequencing reads, such as Amplicon, Target Capture, Metagenome, and Whole genome data. "}}, "target": "demultiplex", "target_idx": 5}
{"id": "mod_diamond_deepclust_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Fast graph-based protein sequence clustering using DIAMOND deepclust (tools: diamond)?", "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.", "bigscape_bigscape": "BiG-SCAPE (Biosynthetic Gene Similarity Clustering and Prospecting Engine) clusters\nbiosynthetic gene clusters", "samtools_coverage": "produces a histogram or table of coverage per chromosome", "custom_clustermetrics": "Computes clustering quality metrics (silhouette, Calinski-Harabasz, Davies-Bouldin) and performs k-sweep analy", "diamond_deepclust": "Fast graph-based protein sequence clustering using DIAMOND deepclust"}}, "target": "diamond_deepclust", "target_idx": 4}
{"id": "mod_manta_somatic_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_makegraph": "Plot Freec output", "orthofinder": "OrthoFinder is a fast, accurate and comprehensive platform for comparative genomics.", "controlfreec_assesssignificance": "Add both Wilcoxon test and Kolmogorov-Smirnov test p-values to each CNV output of FREEC", "manta_somatic": "Manta calls structural variants (SVs) and indels from mapped paired-end sequencing reads. It is optimized for ", "seqtk_seq": "Common transformation operations on FASTA or FASTQ files."}}, "target": "manta_somatic", "target_idx": 3}
{"id": "local_subworkflow_irma_2_1", "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, "Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow IRMA": null}}, "target": "Local subworkflow IRMA", "target_idx": 3}
{"id": "resource_bedtools_genomecov_1", "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_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_cadd_0", "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": {"echtvar/anno": "Annotate a decomposed (and normalized) VCF with an echtvar file", "cadd": "CADD is a tool for scoring the deleteriousness of single nucleotide variants as well as insertion/deletions va", "gatk4/svannotate": "Adds predicted functional consequence, gene overlap, and noncoding element overlap annotations to SV VCF from ", "pbptyper": "Assign PBP type of Streptococcus pneumoniae assemblies", "ribodetector": "Accurate and rapid RiboRNA sequences Detector based on deep learning"}}, "target": "cadd", "target_idx": 1}
{"id": "samplesheet_arch_metagenome_mag_grouped_2_4", "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?", "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": "resource_bakta_baktadbdownload_3", "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_long": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "field_constraint_sample_3_2", "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_bedtools_coverage_0", "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/flank": "Creates two new flanking intervals for each interval in a BED/GFF/VCF file.", "tailfindr": "Estimating poly(A)-tail lengths from basecalled fast5 files produced by Nanopore sequencing of RNA and DNA", "wipertools/fastqwiper": "A tool of the wipertools suite that fixes or wipes out uncompliant reads from FASTQ files", "bedtools/genomecov": "Computes histograms (default), per-base reports (-d) and BEDGRAPH (-bg) summaries of feature coverage (e.g., a"}}, "target": "bedtools/coverage", "target_idx": 0}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_2_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 should the input samplesheet have?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,bam,bai": null}}, "target": "sample,bam", "target_idx": 0}
{"id": "qc_adapt_targeted_amplicon_0_42", "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": "samplesheet_arch_vcf_annotation_pipeline_6_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 are standard for Downstream functional annotation of pre-called VCF files input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,bed": null, "sample,vcf,tbi": null}}, "target": "sample,vcf,tbi", "target_idx": 3}
{"id": "mod_assemblyscan_0", "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": {"abricate/summary": "Screen assemblies for antimicrobial resistance against multiple databases", "tmb/pytmb": "This module calculates Tumor Mutational Burden (TMB) scores from VCF files using the pyTMB tool.", "assemblyscan": "Assembly summary statistics in JSON format", "phispy": "Predict prophages in bacterial genomes", "ale": "ALE: assembly likelihood estimator."}}, "target": "assemblyscan", "target_idx": 2}
{"id": "mod_stecfinder_1", "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": {"stecfinder": "Serotype STEC samples from paired-end reads or assemblies", "ectyper": "In silico prediction of E. coli serotype", "rnaquast": "Assess the quality of an RNAseq assembly with or without a reference genome", "pneumocat": "Determine Streptococcus pneumoniae serotype from Illumina paired-end reads", "agat_sqstatbasic": "Provides basic statistics in text format from a GFF/GTF annotation file"}}, "target": "stecfinder", "target_idx": 0}
{"id": "resource_bedtools_unionbedg_3", "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_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_scrna_10x_v3_3_3", "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": "Define the required samplesheet CSV header schema for Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry) with entry step FASTQC.", "criteria": {"sample,matrix,barcodes,features": null, "sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2,expected_cells": null}}, "target": "sample,fastq_1,fastq_2,expected_cells", "target_idx": 3}
{"id": "mod_panacus_visualize_1", "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": {"panacus_visualize": "Create visualizations from a tsv coverage histogram created with panacus.", "hmmer_eslalipid": "Calculate pairwise percent identity for all sequence pairs in a multiple sequence alignment", "eautils_fastqstats": "Calculate general and per-base statistics from FASTQ files", "agat_sqstatbasic": "Provides basic statistics in text format from a GFF/GTF annotation file", "bam_telomere_estimation": "Estimate telomere length and content from aligned reads using telseq, telogator2, and telomerehunter"}}, "target": "panacus_visualize", "target_idx": 0}
{"id": "schema_std_reportho_2_1", "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,input,output_path,checksum_md5,checksum_sha": null, "sample,fastq_1,fastq_2,sampleID,forwardReads": null, "sample_id,subject_id,species,pcr_target_locus,tissue": null, "id,fasta,query": null}}, "target": "id,fasta,query", "target_idx": 3}
{"id": "mod_rpbp_preparegenome_0", "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": {"rpbp/preparegenome": null, "antismash/antismash": null, "rpbp/estimatemetagenebayesfactors": null, "rpbp/extractorfprofiles": null, "hicexplorer/hicpca": null}}, "target": "rpbp/preparegenome", "target_idx": 0}
{"id": "mod_gedi_indexgenome_1", "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": {"plastid_metagenegenerate": "Compute a metagene profile of read alignments, counts, or quantitative data over one or more regions of intere", "octopusv_svcf2bed": "Converts octopusv SVCF files to the standard BED format", "gedi_indexgenome": "Build a GEDI genome index from a FASTA and GTF for downstream PRICE ORF prediction", "plastid_psite": "Estimate position of ribosomal P-site within ribosome profiling read alignments as a function of read length", "dshbio_splitgff3": "Split features in gzipped GFF3 format"}}, "target": "gedi_indexgenome", "target_idx": 2}
{"id": "samplesheet_arch_cancer_somatic_bam_5_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": "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, "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": "qc_adapt_bulk_multiqc_1_9", "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": "qc_adapt_qc_aggregate_0_49", "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_fgumi_downsample_1", "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": {"fgbio_collectduplexseqmetrics": null, "fgumi_downsample": null, "fgumi_correct": null, "kma_index": null, "crisprcleanr_normalize": null}}, "target": "fgumi_downsample", "target_idx": 1}
{"id": "schema_std_genomeqc_2_1", "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": {"fasta,assembly,ncbi,gff,fastq": null, "sample,fastq_1,fastq_2,strandedness,type": null, "id,fasta,reference,optional_data,template": null, "sample_id,img_directory,parameter_file": null}}, "target": "fasta,assembly,ncbi,gff,fastq", "target_idx": 0}
{"id": "field_constraint_fastq_1_3_9", "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, "type: integer": null, "enum: [auto, forward, reverse, unstranded]": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 1}
{"id": "intent_build_pipeline_6", "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", "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": "resource_aria2_5", "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_low": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_rnafusion_pe_3_2", "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": "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,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": "noul_container_environment_specification_8", "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_mira_influenza_sc2_2_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 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,fastq_2", "target_idx": 0}
{"id": "field_constraint_bai_3_0", "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+\\.tbi$": null, "pattern: ^\\S+\\.crai$": null, "type: boolean": null, "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 3}
{"id": "samplesheet_arch_vcf_annotation_pipeline_0_2", "category": "samplesheet_schema", "state": {"assay": "Downstream functional annotation of pre-called VCF files", "first_step": "ENSEMBLVEP"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Downstream functional annotation of pre-called VCF files?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bed": null, "sample,vcf,tbi": null, "sample,vcf": null}}, "target": "sample,vcf,tbi", "target_idx": 2}
{"id": "mod_catpack_reads_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Taxonomic classification plus read-based abundance estimation from long DNA sequences and metagenome assembled genomes (e.g. contigs, MAGs / bins). (tools: catpack)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"scvitools_solo": "Detect doublets in single-cell RNA-Seq data", "ska_fasta": "Create genome sketch using split k-mers", "catpack_bins": "Taxonomic classification of long DNA sequences and metagenome assembled genomes (e.g. MAGs / bins).", "catpack_download": "Downloads the required files for either Nr or GTDB for building into a CAT database", "catpack_reads": "Taxonomic classification plus read-based abundance estimation from long DNA sequences and metagenome assembled"}}, "target": "catpack_reads", "target_idx": 4}
{"id": "field_constraint_strandedness_3_14", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "strandedness", "validation_type": "categorical_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'strandedness'.", "criteria": {"format: file-path": null, "pattern: ^[0-9]+$": null, "enum: [auto, forward, reverse, unstranded]": null, "type: boolean": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 2}
{"id": "samplesheet_arch_spatial_visium_5_4", "category": "samplesheet_schema", "state": {"assay": "10x Visium spatial transcriptomics with histology image", "first_step": "FASTQC"}, "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,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": "mod_bbmap_index_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode. (tools: bbmap)?", "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.", "segemehl_index": "Generate genome indices for segemehl align", "bismark_deduplicate": "Removes alignments to the same position in the genome\nfrom the Bismark mapping output.", "bbmap_index": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode.", "bbmap_bbsplit": "Split sequencing reads by mapping them to multiple references simultaneously"}}, "target": "bbmap_index", "target_idx": 3}
{"id": "mod_dotseq_dotseq_1", "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": {"dotseq_dotseq": null, "finaletoolkit_adjustwps": null, "plastid_metagenegenerate": null, "bedtools_jaccard": null, "gedi_price": null}}, "target": "dotseq_dotseq", "target_idx": 0}
{"id": "qc_adapt_pe_illumina_fastqc_2_49", "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": "local_subworkflow_checkirma_2_2", "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, "Local subworkflow CHECKIRMA": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Local subworkflow CHECKIRMA", "target_idx": 1}
{"id": "qc_adapt_ont_ultra_long_2_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": "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_exit_code_137_cause_9", "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_bam_2_10", "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+\\.vcf(\\.gz)?$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 3}
{"id": "qc_adapt_illumina_novaseq_1_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": "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_biobambam_bamsormadup_1", "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_single": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_targeted_amplicon_0_28", "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": "samplesheet_arch_spatial_xenium_6_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 are standard for 10x Xenium in situ subcellular spatial RNA transcriptomics input samplesheet?", "criteria": {"sample,vcf": null, "sample,bam": 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": "mod_deepmased_predict_0", "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": {"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", "biomformat/convert": "Convert biom table to different format.\nConversion between text tab-delimited, BIOM-v1 (JSON), and BIOM-v2 (HD", "openms/idmerger": "Merges several idXML files into one idXML file.", "stacks/refmap": "ref_map.pl script from Stacks for the analysis of RAD-seq data when a reference genome is available."}}, "target": "deepmased/predict", "target_idx": 1}
{"id": "mod_controlfreec_makegraph2_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": {"controlfreec_makegraph2": "Plot Freec output", "controlfreec_freec2bed": "Plot Freec output", "controlfreec_freec": "Copy number and genotype annotation from whole genome and whole exome sequencing data", "ataqv_mkarv": "mkarv function of a corresponding ataqv tool", "centrifuger_quantification": "Quantification (taxonomic profiling) of Centrifuger model"}}, "target": "controlfreec_makegraph2", "target_idx": 0}
{"id": "samplesheet_arch_ont_demux_barcodes_7_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": "Which columns should the input samplesheet have for single-end ONT?", "criteria": {"sample,bam": 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": "mod_parabricks_applybqsr_0", "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": {"gatk4/analyzecovariates": "Evaluate and compare base quality score recalibration (BQSR) tables", "parabricks/applybqsr": "NVIDIA Clara Parabricks GPU-accelerated apply Base Quality Score Recalibration (BQSR).", "gatk4/baserecalibrator": "Generate recalibration table for Base Quality Score Recalibration (BQSR)", "hmmer/hmmfetch": "extract hmm from hmm database file or create index for hmm database", "comet": "Comet is an open source tandem mass spectrometry (MS/MS) sequence database search tool"}}, "target": "parabricks/applybqsr", "target_idx": 1}
{"id": "mod_seqtk_trim_0", "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": {"adapterremoval": null, "art/illumina": null, "kallistobustools/count": null, "graphtyper/genotype": null, "seqtk/trim": null}}, "target": "seqtk/trim", "target_idx": 4}
{"id": "field_constraint_bam_1_14", "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+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 2}
{"id": "samplesheet_arch_methylseq_bisulfite_6_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 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": "noul_invalid_process_communication_via_globals_7", "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_gatk4_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": {"dastool_scaffolds2bin": "Helper script to convert a set of bins in fasta format to tabular scaffolds2bin format", "gatk4_applybqsr": "Apply base quality score recalibration (BQSR) to a bam file", "apbs": "Compute biomolecular electrostatics by solving the Poisson-Boltzmann equation\nusing APBS (Adaptive Poisson-Bol", "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"}}, "target": "gatk4_applybqsr", "target_idx": 1}
{"id": "samplesheet_arch_metatranscriptome_denovo_3_4", "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": "Define the required samplesheet CSV header schema for Environmental community metatranscriptomics de novo assembly with entry step FASTQC.", "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": "samplesheet_arch_bacterial_hybrid_assembly_3_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": "Define the required samplesheet CSV header schema for Hybrid bacterial assembly combining short Illumina and long Nanopore reads with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": 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": "resource_busco_phylogenomics_2", "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_long": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "noul_single_hyphen_cli_params_error_6", "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_taxprofiler_shotgun_6_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 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,fastq_1,fastq_2": null, "sample,kraken_db": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 0}
{"id": "intent_ask_question_24", "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", "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": "qc_adapt_ffpe_wes_0_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": "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_sex_1_3", "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": {"type: boolean": null, "enum: [1, 2, other, unknown] (1=male, 2=female)": null, "pattern: ^\\S+\\.gz$": null, "format: file-path": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 1}
{"id": "mod_ampcombi_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool to parse and summarise results from antimicrobial peptides tools and present functional classification. (tools: ampcombi)?", "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", "bam_qc_rnaseq": "Run post-alignment QC tools on RNA-seq BAM files including library complexity\nestimation (Preseq), biotype QC ", "oarfish/alignmentmode": "oarfish is a program for quantifying transcript-level expression from long-read sequencing technologies. Quant", "macrel/contigs": "A tool that mines antimicrobial peptides (AMPs) from (meta)genomes by predicting peptides from genomes (provid", "ampcombi": "A tool to parse and summarise results from antimicrobial peptides tools and present functional classification."}}, "target": "ampcombi", "target_idx": 4}
{"id": "mod_bedops_convert2bed_1", "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", "bcftools_convert": "Converts certain output formats to VCF", "deepsomatic": "DeepSomatic is an extension of deep learning-based variant caller DeepVariant that takes aligned reads (in BAM", "homer_findpeaks": "Find peaks with HOMER suite", "bedops_convert2bed": "Convert BAM/GFF/GTF/GVF/PSL files to bed"}}, "target": "bedops_convert2bed", "target_idx": 4}
{"id": "resource_ascat_1", "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_long": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_germline_lane_split_2_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 should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "lane,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_abricate_summary_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": {"amrfinderplus/update": "Identify antimicrobial resistance in gene or protein sequences", "abricate/summary": "Screen assemblies for antimicrobial resistance against multiple databases", "rmarkdownnotebook": "Render an rmarkdown notebook. Supports parametrization.", "rseqc/innerdistance": "Calculate inner distance between read pairs.", "antismash/antismash": "antiSMASH allows the rapid genome-wide identification, annotation\nand analysis of secondary metabolite biosynt"}}, "target": "abricate/summary", "target_idx": 1}
{"id": "samplesheet_arch_germline_lane_split_4_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": "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, "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": "mod_mmseqs_tsv2exprofiledb_1", "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": {"mmseqs_createindex": "Creates sequence index for mmseqs database", "mmseqs_tsv2exprofiledb": "Conversion of expandable profile to databases to the MMseqs2 databases format", "tagbam": "A tool for tagging BAM files.", "fgumi_correct": "Correct UMIs in a BAM file to a fixed set of known UMIs with fgumi", "mmseqs_createtsv": "Create a tsv file from a query and a target database as well as the result database"}}, "target": "mmseqs_tsv2exprofiledb", "target_idx": 1}
{"id": "mod_anndata_getsize_0", "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", "fastp": "Perform adapter/quality trimming on sequencing reads", "wittyer": "A large variant benchmarking tool analogous to hap.py for small variants.", "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"}}, "target": "anndata/getsize", "target_idx": 4}
{"id": "qc_adapt_ffpe_wes_0_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": "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": "samplesheet_arch_bulk_wes_pe_3_0", "category": "samplesheet_schema", "state": {"assay": "Paired-end Whole Exome Sequencing (WES) target capture", "first_step": "FASTQC"}, "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": "qc_adapt_ont_ultra_long_0_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": "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_ont_ultra_long_2_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": "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_bulk_rnaseq_se_0_4", "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 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": "intent_debug_error_7", "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": "mod_snapaligner_index_0", "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": {"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", "snapaligner/index": "Create a SNAP index for reference genome", "gcta/fastgwa": "Run GCTA fastGWA mixed linear model association analysis with PLINK genotype inputs", "propr/grea": "Perform Gene Ratio Enrichment Analysis"}}, "target": "snapaligner/index", "target_idx": 2}
{"id": "noul_exit_code_137_cause_7", "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_bulk_wgs_pe_4_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": "What samplesheet columns are expected when inputs are: Raw paired-end Illumina WGS FASTQs?", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "samplesheet_arch_bulk_small_rna_5_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": "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": "pipe_all101_taxprofiler_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: 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": {"taxprofiler": null, "createpanelrefs": null, "demo": null, "detaxizer": null, "metapep": null, "ampliseq": null, "mcmicro": null, "variantprioritization": null}}, "target": "taxprofiler", "target_idx": 0}
{"id": "mod_hmmer_hmmsearch_1", "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_hmmstat": null, "vamb_bin": null, "hmmer_hmmbuild": null, "hmmer_hmmsearch": null, "nacho_normalize": null}}, "target": "hmmer_hmmsearch", "target_idx": 3}
{"id": "qc_adapt_pe_illumina_fastqc_0_14", "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_hipstr_1", "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": {"expansionhunterdenovo_profile": null, "hipstr": null, "svdb_build": null, "strdrop_build": null, "octopusv_svcf2vcf": null}}, "target": "hipstr", "target_idx": 1}
{"id": "samplesheet_arch_bulk_rnaseq_se_1_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": "Which columns should the samplesheet have for Single-end Illumina RNA-seq with strandedness?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1": null, "sample,fastq_1,strandedness": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 3}
{"id": "samplesheet_arch_pacbio_hifi_wgs_5_4", "category": "samplesheet_schema", "state": {"assay": "Long-read Pacific Biosciences HiFi sequencing", "first_step": "HIFIADAPTERFILT"}, "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,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "resource_abricate_summary_3", "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_medium": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "resource_bedtools_subtract_2", "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_high": null, "process_long": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_seqkit_head_1", "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": {"seqkit_head": null, "bbmap_filterbyname": null, "plasmidfinder": null, "pretextsnapshot": null, "biscuit_bsconv": null}}, "target": "seqkit_head", "target_idx": 0}
{"id": "mod_hisat2_extractsplicesites_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extracts splicing sites from a gtf files (tools: hisat2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hisat2/extractsplicesites": "Extracts splicing sites from a gtf files", "regtools/junctionsextract": "Extract exon-exon junctions from an RNAseq BAM file. The output is a BED file in the BED12 format.", "leafcutter/clusterregtools": "Cluster RNA-seq junction reads extracted by regtools and refine them based on read counts and ratios for alter", "sentieon/qualcal": "Generate recalibration table and optionally perform base quality recalibration", "modkit/pileup": "A bioinformatics tool for working with modified bases"}}, "target": "hisat2/extractsplicesites", "target_idx": 0}
{"id": "local_subworkflow_daisribosome_1_5", "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": {"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": "noul_mix_operator_async_emission_22", "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_helitronscanner_draw_0", "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": null, "alignoth": null, "gatk4/mutect2": null, "agat/spfilterfeaturefromkilllist": null, "fasta_binning_concoct": null}}, "target": "helitronscanner/draw", "target_idx": 0}
{"id": "mod_fusionreport_detect_1", "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": {"biobambam_bamsormadup": "Parallel sorting and duplicate marking", "fusionreport_detect": "fusionreport_detect", "csvtk_sort": "Sort  CSV (or TSV) tables", "htsnimtools_vcfcheck": "This tools takes a background VCF, such as gnomad, that has full genome (though in some cases, users will inst", "merqury_merqury": "k-mer based assembly evaluation."}}, "target": "fusionreport_detect", "target_idx": 1}
{"id": "qc_adapt_pacbio_hifi_0_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": "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_bulk_multiqc_0_22", "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": "mod_bcftools_reheader_0", "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": {"aardvark/merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF.", "pharmcat/matcher": "The Named Allele Matcher is responsible for calling diplotypes from variant call data.\nWhile it is designed to", "rustqc": "All-in-one RNA-seq post-alignment QC replacing dupRadar, featureCounts biotype QC, RSeQC, Preseq, Qualimap, an", "bcftools/reheader": "Reheader a VCF file", "aardvark/compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF."}}, "target": "bcftools/reheader", "target_idx": 3}
{"id": "mod_hicexplorer_hicpca_1", "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": {"hicexplorer_hicpca": "Computes PCA eigenvectors for a Hi-C matrix.", "plink2_pca": "Perform PCA analysis using PLINK", "openms_idscoreswitcher": "Switches between different scores of peptide or protein hits in identification data", "csvtk_sort": "Sort  CSV (or TSV) tables", "deeptools_plotpca": "Generates principal component analysis (PCA) plot using a compressed matrix generated by multibamsummary or mu"}}, "target": "hicexplorer_hicpca", "target_idx": 0}
{"id": "subworkflow_pkg_bam_dedup_stats_samtools_umicollapse_2", "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": {"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, "Leave them out": null}}, "target": "Use nf-core subworkflow bam_dedup_stats_samtools_umicollapse", "target_idx": 2}
{"id": "samplesheet_arch_cancer_somatic_tn_5_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": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Somatic cancer variant calling with tumor-normal pairs.", "criteria": {"sample,fastq_1": null, "patient,sample,status,bam,bai": 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": "mod_vcf2zarr_convert_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_annotate": "Add or remove annotations.", "vcf2zarr_convert": "Convert VCF data to the VCF Zarr specification reliably, in parallel or distributed over a cluster", "seqsero2": "Salmonella serotype prediction from reads and assemblies", "rpbp_selectperiodicoffsets": "Pick the single best P-site offset for each read length from the\nper-(length, offset) Bayes factor table produ", "atlas_call": "generate VCF file from a BAM file using various calling methods"}}, "target": "vcf2zarr_convert", "target_idx": 1}
{"id": "resource_barrnap_1", "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_high": null, "process_single": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "subworkflow_pkg_bam_stats_samtools_1", "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, "Local subworkflow BAM_STATS_SAMTOOLS": null, "Leave them out": null, "Use nf-core subworkflow bam_stats_samtools": null}}, "target": "Use nf-core subworkflow bam_stats_samtools", "target_idx": 3}
{"id": "mod_abacas_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Contiguate draft genome assembly (tools: abacas)?", "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", "agat/convertspgff2gtf": "Converts a GFF/GTF file into a proper GTF file", "pypgx/createinputvcf": "Call SNVs/indels from BAM files for all target genes.", "abacas": "Contiguate draft genome assembly", "bbmap/pileup": "Calculates per-scaffold or per-base coverage information from an unsorted sam or bam file."}}, "target": "abacas", "target_idx": 3}
{"id": "field_constraint_sample_2_14", "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, "format: file-path": null, "type: integer": null, "enum: [0, 1]": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 0}
{"id": "resource_bcftools_sort_3", "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_low": null, "process_high": null, "process_medium": null, "process_single": null}}, "target": "process_medium", "target_idx": 2}
{"id": "resource_bedtools_sort_1", "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_medium": null, "process_low": null, "process_high": null, "process_long": null}}, "target": "process_medium", "target_idx": 0}
{"id": "resource_biscuit_mergecg_0", "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_low": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_bcftools_convert_1", "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_single": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_singlecell_parse_splitseq_3_4", "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": "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,bam": 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_0_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": "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_gtdbtk_classifywf_0", "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": {"gatk4/getpileupsummaries": "Summarizes counts of reads that support reference, alternate and other alleles for given sites. Results can be", "popscle/dscpileup": "Software to pileup reads and corresponding base quality for each overlapping SNPs and each barcode.", "gtdbtk/classifywf": "GTDB-Tk is a software toolkit for assigning objective taxonomic classifications to bacterial and archaeal geno", "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)."}}, "target": "gtdbtk/classifywf", "target_idx": 2}
{"id": "noul_subworkflow_structural_blocks_23", "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": "pipe_all101_epitopeprediction_0", "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": {"proteogenomicsdb": null, "atacseq": null, "mhcquant": null, "pangenome": null, "airrflow": null, "ampliseq": null, "epitopeprediction": null, "spatialaxe": null, "proteinannotator": null, "proteinfamilies": null}}, "target": "epitopeprediction", "target_idx": 6}
{"id": "mod_kraken2_add_0", "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": {"bracken/combinebrackenoutputs": "Combine output of metagenomic samples analyzed by bracken.", "methurator/gtestimator": "Run estimator for DNA methylation sequencing saturation.", "kraken2/add": "Adds fasta files to a Kraken2 taxonomic database", "binette": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning", "fastq_align_bwaaln": "Align FASTQ files against reference genome with the bwa aln short-read aligner producing a sorted and indexed "}}, "target": "kraken2/add", "target_idx": 2}
{"id": "mod_caddsv_run_1", "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": {"annotsv_installannotations": "Install the AnnotSV annotations", "caddsv_run": "Score structural variants with CADD-SV.", "snapaligner_index": "Create a SNAP index for reference genome", "sigprofiler": "mutational signature deconvolution of cancer cells", "annotsv_annotsv": "Annotation and Ranking of Structural Variation"}}, "target": "caddsv_run", "target_idx": 1}
{"id": "samplesheet_arch_cancer_tumor_only_6_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 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,fastq_2": null, "sample,bam": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 1}
{"id": "field_constraint_status_2_10", "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": {"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_ivar_variants_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Call variants from a BAM file using iVar (tools: ivar)?", "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", "freyja_boot": "Bootstrap sample demixing by resampling each site based on a multinomial distribution of read depth across all", "ivar_variants": "Call variants from a BAM file using iVar", "cutesv": "structural-variant calling with cutesv", "ivar_consensus": "Generate a consensus sequence from a BAM file using iVar"}}, "target": "ivar_variants", "target_idx": 2}
{"id": "samplesheet_arch_cageseq_transcription_3_0", "category": "samplesheet_schema", "state": {"assay": "CAGE-seq 5-prime capped transcript end sequencing", "first_step": "FASTQC"}, "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,tss_bed": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "mod_td2_predict_1", "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": {"ribotish_predict": "Quality control of riboseq bam data", "td2_predict": "TD2 identifies candidate coding regions within transcript sequences, such as those generated by de novo RNA-Se", "bam_sort_stats_samtools": "Sort SAM/BAM/CRAM file", "td2_longorfs": "TD2 identifies candidate coding regions within transcript sequences, such as those generated by de novo RNA-Se", "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"}}, "target": "td2_predict", "target_idx": 1}
{"id": "mod_shigeifinder_1", "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": {"shigeifinder": "Determine Shigella serotype from assemblies or Illumina paired-end reads", "svdss_index": "Index a reference genome FASTA file using SVDSS (via ropebwt3), producing either an FMD or FMR index for use w", "adapterremovalfixprefix": "Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with", "stare": "Framework that scores enhancer–gene interactions using the Activity-By-Contact model and derives transcription", "art_illumina": "Simulation tool to generate synthetic Illumina next-generation sequencing reads"}}, "target": "shigeifinder", "target_idx": 0}
{"id": "samplesheet_arch_cancer_somatic_bam_1_2", "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 Somatic tumor-normal calling from pre-aligned BAM files?", "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": "samplesheet_arch_bacterial_hybrid_assembly_1_4", "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 samplesheet have for Hybrid bacterial assembly combining short Illumina and long Nanopore reads?", "criteria": {"sample,fasta": 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": "qc_adapt_pacbio_hifi_1_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": "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": "samplesheet_arch_metagenome_mag_grouped_1_5", "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 samplesheet have for Metagenomic MAG assembly with comparative groups?", "criteria": {"sample,fasta": 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": "qc_adapt_ffpe_wes_2_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": "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_cooler_balance_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run matrix balancing on a cool file (tools: cooler)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"lofreq/call": "Lofreq subcommand to call low frequency variants from alignments", "cooler/balance": "Run matrix balancing on a cool file", "cooler/digest": "Generate fragment-delimited genomic bins", "wipertools/fastqwiper": "A tool of the wipertools suite that fixes or wipes out uncompliant reads from FASTQ files", "cooler/zoomify": "Generate a multi-resolution cooler file by coarsening"}}, "target": "cooler/balance", "target_idx": 1}
{"id": "mod_gapseq_fill_1", "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": {"gapseq_requestdb": "Download gapseq reference sequence database for metabolic pathway prediction", "gapseq_fill": "Perform gap filling on draft metabolic model", "openmsthirdparty_cometadapter": "Annotates MS/MS spectra using Comet.", "gapseq_medium": "Predict growth medium from a draft model and pathway predictions", "variantbam": "Filtering, downsampling and profiling alignments in BAM/CRAM formats"}}, "target": "gapseq_fill", "target_idx": 1}
{"id": "field_constraint_phenotype_3_7", "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": "mod_ea-utils_gtf2bed_0", "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": {"agat/spkeeplongestisoform": "Filters GFF records to keep only the longest isoform per gene", "seqfu/derep": "Dereplicate FASTX sequences, removing duplicate sequences and printing the number of identical sequences in th", "kmcp/merge": "Merge search results from multiple databases.", "agat/spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "ea-utils/gtf2bed": "Convert a GTF/GFF annotation file to BED12 format"}}, "target": "ea-utils/gtf2bed", "target_idx": 4}
{"id": "schema_std_bacass_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/bacass. Description: Simple bacterial assembly and annotation pipeline.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/bacass.", "criteria": {"sample_id,img_directory,parameter_file": null, "sample,fastq_1,fastq_2,sampleID,forwardReads": null, "ID,R1,R2,LongFastQ,Fast5": null, "id,test_vcf,test_regions,caller,subsample": null}}, "target": "ID,R1,R2,LongFastQ,Fast5", "target_idx": 2}
{"id": "resource_angsd_dosaf_1", "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_single": null, "process_low": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "noul_confusing_combine_with_mix_semantics_9", "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_ribocode_prepare_1", "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": {"vardictjava": "The Java port of the VarDict variant caller", "ribocode_gtfupdate": "Update GTF annotation file for RiboCode compatibility", "ribocode_prepare": "Prepare the annotation files for RiboCode ORF calling", "gatk4_applybqsr": "Apply base quality score recalibration (BQSR) to a bam file", "ribocode_ribocode": "Call ORFs with RiboCode from Ribo-Seq data"}}, "target": "ribocode_prepare", "target_idx": 2}
{"id": "samplesheet_arch_scrna_10x_v3_6_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 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,matrix,barcodes,features": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,expected_cells", "target_idx": 0}
{"id": "mod_genmod_annotate_1", "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": {"bcftools_annotate": "Add or remove annotations.", "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", "pypgx_createinputvcf": "Call SNVs/indels from BAM files for all target genes.", "fastqe": "fastqe is a bioinformatics command line tool that uses emojis to represent and analyze genomic data."}}, "target": "genmod_annotate", "target_idx": 2}
{"id": "resource_bedtools_genomecov_3", "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_single": null, "process_high": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_riboseq_profiling_4_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": "What samplesheet columns are expected when inputs are: Single-end ribosome protected RNA fragments (RPFs) with strandedness?", "criteria": {"sample,cdna_fasta": null, "sample,fastq_1,strandedness": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 1}
{"id": "pipe_all101_multiplesequencealign_5", "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": {"drugresponseeval": "Pipeline for testing drug response prediction models in a statistically and biologically sound way. [cell-lines, cross-v", "multiplesequencealign": "A pipeline to run and systematically evaluate Multiple Sequence Alignment (MSA) methods.", "magmap": "Best-practice analysis pipeline for mapping reads to a (large) collections of genomes", "readsimulator": "A pipeline to simulate sequencing reads, such as Amplicon, Target Capture, Metagenome, and Whole genome data. ", "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]", "variantbenchmarking": "Pipeline to evaluate and validate the accuracy of variant calling methods in genomic research [benchmark, small-variants", "fastqrepair": "A pipeline that can be used to recover corrupted FASTQ.gz files, drop or fix uncompliant reads, remove unpaired reads, a"}}, "target": "multiplesequencealign", "target_idx": 1}
{"id": "mod_graphtyper_genotype_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": {"xeniumranger_relabel": "The xeniumranger relabel module allows you to change the gene labels applied to decoded transcripts.", "jvarkit_vcffilterjdk": "Filtering VCF with dynamically-compiled java expressions", "igvreports": "A Python application to generate self-contained HTML reports for variant review and other genomic applications", "sambamba_depth": "Outputs a coverage file from bam files", "graphtyper_genotype": "Tools for population-scale genotyping using pangenome graphs."}}, "target": "graphtyper_genotype", "target_idx": 4}
{"id": "mod_bamtofastq10x_1", "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": {"fmhfunprofiler": "Functionally profile metagenomic samples using FracMinHash sketches against KEGG database references.", "bamtofastq10x": "Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ATAC, Cell Ranger DNA, and Lon", "ascat": "copy number profiles of tumour cells.", "bamclipper": "This module is used to clip primer sequences from your alignments.", "oarfish_alignmentmode": "oarfish is a program for quantifying transcript-level expression from long-read sequencing technologies. Quant"}}, "target": "bamtofastq10x", "target_idx": 1}
{"id": "field_constraint_phenotype_2_4", "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": "field_constraint_status_0_14", "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, "format: file-path": null, "enum: [auto, forward, reverse]": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 1}
{"id": "mod_vcflib_vcffilter_0", "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": {"arcane/filter": "Filter GTF annotations and genome sequence for alignment-free single-cell RNA-seq quantification with Arcane", "vcflib/vcffilter": "Command line tools for parsing and manipulating VCF files.", "anota2seq/anota2seqrun": "Generally applicable transcriptome-wide analysis of translational efficiency using anota2seq", "agat/spkeeplongestisoform": "Filters GFF records to keep only the longest isoform per gene", "samtools/fixmate": "Samtools fixmate is a tool that can fill in information (insert size, cigar, mapq) about paired end reads onto"}}, "target": "vcflib/vcffilter", "target_idx": 1}
{"id": "mod_vcf_phase_shapeit5_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subworkflow to phase a reference panel VCF file using SHAPEIT5.\nThe panel is first chunked by chromosome by glimpse2/chunk,\nthen genotypes are phased with shapeit5/phasecommon and\nfinally the chunks are merged back together by shapeit5/ligate by chromosomes.\nMeta map of all channels 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_phase_shapeit5)?", "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.", "mmseqs_taxonomy": "Computes the lowest common ancestor by identifying the query sequence homologs against the target database.", "bcftools_convert": "Converts certain output formats to VCF", "vcf_phase_shapeit5": "Subworkflow to phase a reference panel VCF file using SHAPEIT5.\nThe panel is first chunked by chromosome by gl", "annotsv_annotsv": "Annotation and Ranking of Structural Variation"}}, "target": "vcf_phase_shapeit5", "target_idx": 3}
{"id": "mod_bam_variant_calling_sort_freebayes_bcftools_0", "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": {"mmseqs/createtsv": "Create a tsv file from a query and a target database as well as the result database", "bam_variant_calling_sort_freebayes_bcftools": "Call variants using freebayes, then sort and index", "agat/spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "ferrohgvs/parse": "Parse and validate HGVS variant descriptions with ferro", "ferrohgvs/normalize": "Normalize HGVS variant descriptions to canonical form with ferro"}}, "target": "bam_variant_calling_sort_freebayes_bcftools", "target_idx": 1}
{"id": "resource_bedops_convert2bed_3", "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": "schema_std_raredisease_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/raredisease", "description": "Call and score variants from WGS/WES of rare disease patients.", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/raredisease?", "criteria": {"sample,short_reads_fastq_1,short_reads_fastq_2,long_reads_fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,bam,bai": null, "patient,sample,vcf,status,cna": null}}, "target": "sample,fastq_1,fastq_2,bam,bai", "target_idx": 2}
{"id": "mod_csvtk_mutate2_1", "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": {"fgumi_clip": null, "minimac4_compressref": null, "annotsv_annotsv": null, "csvtk_mutate2": null, "csvtk_concat": null}}, "target": "csvtk_mutate2", "target_idx": 3}
{"id": "samplesheet_arch_riboseq_profiling_2_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 should the input samplesheet have?", "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": "mod_amrfinderplus_run_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": {"abritamr/run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes", "abricate/run": "Screen assemblies for antimicrobial resistance against multiple databases", "amrfinderplus/run": "Identify antimicrobial resistance in gene or protein sequences", "stringtie/stringtie": "Transcript assembly and quantification for RNA-Se", "skani/sketch": "Storing skani sketches/indices on disk."}}, "target": "amrfinderplus/run", "target_idx": 2}
{"id": "mod_fastq_align_chromap_0", "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": {"bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files.", "picard/sortvcf": "Sorts vcf files", "fastq_align_chromap": "Align high throughput chromatin profiles using Chromap, updating readgroups if neccessary and then sort with s", "liftoff": "Uses Liftoff to accurately map annotations in GFF or GTF between assemblies of the same,\nor closely-related sp", "ampcombi": "A tool to parse and summarise results from antimicrobial peptides tools and present functional classification."}}, "target": "fastq_align_chromap", "target_idx": 2}
{"id": "qc_adapt_singlecell_multiqc_1_21", "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": "subworkflow_pkg_opt_flip_track_stat_1", "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": {"Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow opt_flip_track_stat": null, "Local subworkflow OPT_FLIP_TRACK_STAT": null}}, "target": "Use nf-core subworkflow opt_flip_track_stat", "target_idx": 2}
{"id": "mod_lofreq_indelqual_1", "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": {"aardvark_compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "kma_index": "This module wraps the index module of the KMA alignment tool.", "atlas_call": "generate VCF file from a BAM file using various calling methods", "gcta_reml": "Run univariate REML heritability estimation with a dense GRM", "lofreq_indelqual": "Inserts indel qualities in a BAM file"}}, "target": "lofreq_indelqual", "target_idx": 4}
{"id": "mod_mm2plus_index_1", "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": {"catpack_reads": "Taxonomic classification plus read-based abundance estimation from long DNA sequences and metagenome assembled", "shapeit5_switch": "Program to compute switch error rate and genotyping error rate given simulated or trio data.", "bismark_genomepreparation": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for ali", "mm2plus_index": "Provides fasta index required by mm2plus alignment.", "bowtie_build": "Create bowtie index for reference genome"}}, "target": "mm2plus_index", "target_idx": 3}
{"id": "resource_bbmap_bbsplit_1", "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": "samplesheet_arch_mira_influenza_sc2_4_2", "category": "samplesheet_schema", "state": {"assay": "Custom MIRA-NF Influenza / SC2 pipeline", "first_step": "INPUT_CHECK"}, "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,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_openmsthirdparty_cometadapter_0", "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.", "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", "macse/refinealignment": "improves the input nucleotide alignment in a codon-aware manner", "bcftools/split": "Split a vcf file into files per chromosome"}}, "target": "openmsthirdparty/cometadapter", "target_idx": 0}
{"id": "mod_octopusv_svcf2bed_1", "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": {"gatk4_createsomaticpanelofnormals": "Create a panel of normals constraining germline and artifactual sites for use with mutect2.", "bamtools_convert": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "octopusv_merge": "Merge and harmonize structural variant calls from multiple samples.", "octopusv_svcf2bed": "Converts octopusv SVCF files to the standard BED format", "deeptools_plotfingerprint": "plots cumulative reads coverages by BAM file"}}, "target": "octopusv_svcf2bed", "target_idx": 3}
{"id": "mod_clame_1", "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": {"bedtools_sort": "Sorts a feature file by chromosome and other criteria.", "elprep_filter": "Filter, sort and markdup sam/bam files, with optional BQSR and variant calling.", "bcftools_plotvcfstats": "Plots the output of bcftools stats", "clame": "binning of metagenomic sequences", "fgumi_fastq": "Convert a BAM file to interleaved FASTQ format with fgumi"}}, "target": "clame", "target_idx": 3}
{"id": "mod_gtf_hybridmerge_gffcompare_0", "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": {"trtools/dumpstr": null, "ectyper": null, "gtf_hybridmerge_gffcompare": null, "agat/spaddintrons": null, "agat/convertspgff2gtf": null}}, "target": "gtf_hybridmerge_gffcompare", "target_idx": 2}
{"id": "resource_bbmap_repair_3", "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_low": null, "process_single": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_gatk4_cnnscorevariants_1", "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": {"mirtop_gff": "mirtop gff generates the GFF3 adapter format to capture miRNA variations", "gatk4_cnnscorevariants": "Apply a Convolutional Neural Net to filter annotated variants", "gatk4_annotateintervals": "Annotates intervals with GC content, mappability, and segmental-duplication content", "repeatmodeler_repeatmodeler": "Performs de novo transposable element (TE) family identification with RepeatModeler", "gatk4_analyzecovariates": "Evaluate and compare base quality score recalibration (BQSR) tables"}}, "target": "gatk4_cnnscorevariants", "target_idx": 1}
{"id": "schema_std_longraredisease_2_0", "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": {"sample,fastq_1,fastq_2,strandedness,condition": null, "fastq_1,fastq_2,group,replicate,md5_1": null, "sample,fasta,protein,gbk,gff": null, "family_id,sample,file_path,hpo_terms,sex": null}}, "target": "family_id,sample,file_path,hpo_terms,sex", "target_idx": 3}
{"id": "mod_picard_collectalignmentsummarymetrics_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Collect metrics about the alignment summary of a paired-end library. (tools: picard)?", "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", "picard/collectalignmentsummarymetrics": "Collect metrics about the alignment summary of a paired-end library.", "rastair/methylkit": "Parses rastair call output and converts it into a MethylKit-compatible format.", "custom/clustermetrics": "Computes clustering quality metrics (silhouette, Calinski-Harabasz, Davies-Bouldin) and performs k-sweep analy", "fgumi/duplexmetrics": "Collects a suite of metrics to QC duplex sequencing data"}}, "target": "picard/collectalignmentsummarymetrics", "target_idx": 1}
{"id": "qc_adapt_targeted_amplicon_0_2", "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_invalid_process_communication_via_globals_4", "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": "noul_subworkflow_structural_blocks_2", "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_braker3_0", "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": {"helitronscanner/scan": null, "abacas": null, "braker3": null, "agat/convertbed2gff": null, "gatk4/genomicsdbimport": null}}, "target": "braker3", "target_idx": 2}
{"id": "samplesheet_arch_dual_rnaseq_host_pathogen_0_2", "category": "samplesheet_schema", "state": {"assay": "Dual RNA-seq simultaneous host and pathogen transcriptomics", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Dual RNA-seq simultaneous host and pathogen transcriptomics?", "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": "field_constraint_bai_3_4", "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$": null, "type: boolean": null, "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "pattern: ^\\S+\\.tbi$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 2}
{"id": "local_subworkflow_nextclade_2_3", "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, "Leave them out": null, "Use nf-core subworkflow nextclade": null}}, "target": "Local subworkflow NEXTCLADE", "target_idx": 0}
{"id": "samplesheet_arch_bulk_rnaseq_pe_0_2", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq with strandedness", "first_step": "FASTQC"}, "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,fastq_2,group": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 3}
{"id": "samplesheet_arch_riboseq_profiling_3_3", "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": "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,cdna_fasta": null, "sample,fastq_1,strandedness": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 3}
{"id": "mod_qsv_cat_1", "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": {"untar": null, "agat_convertspgff2tsv": null, "qsv_cat": null, "find_concatenate": null, "utils_nextflow_pipeline": null}}, "target": "qsv_cat", "target_idx": 2}
{"id": "noul_channel_operator_map_17", "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": "samplesheet_arch_methylseq_bisulfite_1_5", "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 samplesheet have for Whole-Genome Bisulfite Sequencing (WGBS / EM-seq)?", "criteria": {"sample,cpg,methylation": null, "sample,vcf": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "samplesheet_arch_cancer_tumor_only_7_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": "Which columns should the samplesheet have for tumor-normal pairs?", "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": "noul_include_modular_process_syntax_22", "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_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": "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": "samplesheet_arch_scrna_10x_v3_6_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 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,matrix,barcodes,features": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,expected_cells", "target_idx": 0}
{"id": "subworkflow_pkg_fastq_contam_seqtk_kraken_1", "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": {"Local subworkflow FASTQ_CONTAM_SEQTK_KRAKEN": null, "Leave them out": 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": "resource_agat_spkeeplongestisoform_0", "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_long": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_rnafusion_pe_0_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": "Which columns should the input samplesheet have for: RNA gene fusion detection (Arriba, STAR-Fusion)?", "criteria": {"sample,fusion_bed": 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_mdust_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: mdust from DFCI Gene Indices Software Tools for masking low-complexity DNA sequences (tools: mdust)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"motus_merge": null, "alignoth": null, "cellrangeratac_mkref": null, "agat_spfilterbyorfsize": null, "mdust": null}}, "target": "mdust", "target_idx": 4}
{"id": "qc_adapt_pe_illumina_fastqc_2_32", "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": "resource_bedtools_genomecov_4", "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_single": null, "process_medium": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_angsd_contamination_3", "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_long": null, "process_medium": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "intent_ask_question_5", "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, "debug_error": null, "ask_question": null}}, "target": "ask_question", "target_idx": 3}
{"id": "resource_bbmap_pileup_3", "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_low": null, "process_high": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_bam_vcf_impute_glimpse2_1", "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": {"glimpse2_ligate": "Ligatation of multiple phased BCF/VCF files into a single whole chromosome file.\nGLIMPSE2 is run in chunks tha", "vt_decompose": "decomposes multiallelic variants into biallelic in a VCF file.", "bam_vcf_impute_glimpse2": "Subworkflow to impute VCF and BAM files using GLIMPSE V2 software. The subworkflow\ntakes VCF files, phased ref", "glimpse_ligate": "Concatenates imputation chunks in a single VCF/BCF file ligating phased information.", "krona_ktimporttext": "Creates a Krona chart from text files listing quantities and lineages."}}, "target": "bam_vcf_impute_glimpse2", "target_idx": 2}
{"id": "pipe_core10_ampliseq_2_bare", "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": {"chipseq": null, "scrnaseq": null, "rnaseq": null, "taxprofiler": null, "atacseq": null, "mag": null, "eager": null, "sarek": null, "viralrecon": null, "ampliseq": null}}, "target": "ampliseq", "target_idx": 9}
{"id": "mod_humid_1", "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": {"fgbio_zipperbams": null, "humid": null, "medaka": null, "chelae_trim": null, "salmon_index": null}}, "target": "humid", "target_idx": 1}
{"id": "mod_vrhyme_vrhyme_0", "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": {"skani/sketch": "Storing skani sketches/indices on disk.", "comebin/runcomebin": "Effective binning of metagenomic contigs using COntrastive Multi-viEw representation learning", "concoct/concoct": "Unsupervised binning of metagenomic contigs by using nucleotide composition - kmer frequencies - and coverage ", "vrhyme/vrhyme": "Binning virus genomes from metagenomes", "bismark/deduplicate": "Removes alignments to the same position in the genome\nfrom the Bismark mapping output."}}, "target": "vrhyme/vrhyme", "target_idx": 3}
{"id": "field_constraint_fastq_1_2_4", "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, "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": "noul_channel_operator_map_4", "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_bacterial_hybrid_assembly_7_4", "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 for single-end ONT?", "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_bftools_showinf_2", "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_medium": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_fastq_ngscheckmate_1", "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", "tcoffee_irmsd": "Computes the irmsd score for a given alignment and the structures.", "adapterremoval": "Trim sequencing adapters and collapse overlapping reads", "tcoffee_regressive": "Aligns sequences using the regressive algorithm as implemented in the T_COFFEE package", "ngscheckmate_vafncm": "Determining whether sequencing data comes from the same individual by using SNP matching. This module generate"}}, "target": "fastq_ngscheckmate", "target_idx": 0}
{"id": "qc_adapt_targeted_amplicon_0_4", "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": "subworkflow_pkg_bam_methyldackel_1", "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": {"Leave them out": null, "Use nf-core subworkflow bam_methyldackel": null, "Local subworkflow BAM_METHYLDACKEL": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow bam_methyldackel", "target_idx": 1}
{"id": "mod_picard_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": {"checkm2/predict": "CheckM2 bin quality prediction", "ampcombi": "A tool to parse and summarise results from antimicrobial peptides tools and present functional classification.", "picard/bedtointervallist": "Creates an interval list from a bed file and a reference dict", "agat/convertbed2gff": "Takes a bed12 file and converts to a GFF3 file", "bamtools/convert": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files."}}, "target": "picard/bedtointervallist", "target_idx": 2}
{"id": "qc_adapt_ont_ultra_long_1_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": "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_bulk_multiqc_2_18", "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": "mod_ultra_align_1", "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": {"deeptools_bigwigcompare": "Compare two bigWig files based on the number of mapped reads", "ultra_align": "uLTRA aligner - A wrapper around minimap2 to improve small exon detection - Map reads on genome", "bcftools_pluginimputeinfo": "Adds imputation information metrics to the INFO field based on selected FORMAT tags. Only the IMPUTE2 INFO met", "ultra_pipeline": "uLTRA aligner - A wrapper around minimap2 to improve small exon detection", "ampcombi2_parsetables": "A submodule that parses and standardizes the results from various antimicrobial peptide identification tools."}}, "target": "ultra_align", "target_idx": 1}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_7_1", "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 are standard for PacBio HiFi input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,bam", "target_idx": 1}
{"id": "field_constraint_sex_1_13", "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": {"type: boolean": null, "enum: [1, 2, other, unknown] (1=male, 2=female)": null, "format: file-path": null, "pattern: ^\\S+\\.gz$": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 1}
{"id": "samplesheet_arch_ampliseq_its_fungal_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/ampliseq --input samplesheet.csv (Assay: Fungal ITS1/ITS2 marker gene amplicon surveillance)", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/ampliseq, determine the input samplesheet column structure for: Fungal ITS1/ITS2 marker gene amplicon surveillance.", "criteria": {"sample,primer_its1,primer_its2": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "field_constraint_bam_1_7", "category": "samplesheet_schema", "state": {"column": "bam", "purpose": "Path to aligned binary sequence alignment (BAM) file"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'bam' (Path to aligned binary sequence alignment (BAM) file).", "criteria": {"pattern: ^\\S+\\.vcf(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null, "format: uri": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 1}
{"id": "qc_adapt_singlecell_multiqc_2_19", "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": "noul_modular_subworkflow_composition_21", "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_purecn_normaldb_1", "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": {"skani_search": "Memory-efficient ANI database queries with skani.", "svtk_countsvtypes": "Count the instances of each SVTYPE observed in each sample in a VCF.", "purecn_normaldb": "Build a normal database for coverage normalization from all the (GC-normalized) normal coverage files. N.B. as", "purecn_intervalfile": "Generate on and off-target intervals for PureCN from a list of targets", "purecn_coverage": "Calculate intervals coverage for each sample. N.B. the tool can not handle staging files with symlinks, stageI"}}, "target": "purecn_normaldb", "target_idx": 2}
{"id": "resource_bamtofastq10x_5", "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_long": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "qc_adapt_pacbio_hifi_1_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": "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": "core_tool_cellranger_bare_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": {"seurat": null, "alevin": null, "starsolo": null, "kallisto_bustools": null, "cellranger": null}}, "target": "cellranger", "target_idx": 4}
{"id": "qc_adapt_ont_ultra_long_1_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": "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": "samplesheet_arch_cancer_tumor_only_7_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": "Which columns should the samplesheet have for tumor-normal pairs?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "patient,normal,tumor": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 0}
{"id": "resource_bioawk_5", "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_low": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "pipe_all101_smrnaseq_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: 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": {"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]", "smrnaseq": "A small-RNA sequencing analysis pipeline [small-rna, smrna-seq]", "callingcards": "A pipeline for processing calling cards data", "riboseq": "Pipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data.", "imcyto": "Image Mass Cytometry analysis pipeline [cytometry, image-analysis, image-processing]", "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", "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]"}}, "target": "smrnaseq", "target_idx": 2}
{"id": "mod_strobealign_0", "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": {"busco/phylogenomics": "Construct species phylogenies using BUSCO proteins", "strobealign": "Align short reads using dynamic seed size with strobemers", "fastq_align_dna": "Align fastq files to a reference genome", "smncopynumbercaller": "tool to call the copy number of full-length SMN1, full-length SMN2, as well as SMN2Δ7–8 (SMN2 with a deletion ", "umitools/group": "Group reads based on their UMI and mapping coordinates"}}, "target": "strobealign", "target_idx": 1}
{"id": "qc_adapt_qc_aggregate_0_39", "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_truvari_consistency_1", "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": {"hmmcopy_generatemap": "Perl script (generateMap.pl) generates the mappability of a genome given a certain size of reads, for input to", "odgi_unchop": "Merge unitigs into a single node preserving the node order.", "caddsv_get": "Download CADD-SV annotation resources or SegmentNT model files.", "dysgu_run": "Dysgu calls structural variants (SVs) from mapped sequencing reads. It is designed for accurate and efficient ", "truvari_consistency": "Over multiple vcfs, calculate their intersection/consistency."}}, "target": "truvari_consistency", "target_idx": 4}
{"id": "resource_bedtools_coverage_2", "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_medium": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_rbt_vcfsplit_0", "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/spmergeannotations": null, "rbt/vcfsplit": null, "admixture": null, "agat/spextractsequences": null, "wisecondorx/predict": null}}, "target": "rbt/vcfsplit", "target_idx": 1}
{"id": "field_constraint_bai_1_2", "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, "type: boolean": null, "pattern: ^\\S+\\.tbi$": null, "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 3}
{"id": "mod_kaiju_kaiju2krona_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert Kaiju's tab-separated output file into a tab-separated text file which can be imported into Krona. (tools: kaiju)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"kaiju_kaiju2krona": "Convert Kaiju's tab-separated output file into a tab-separated text file which can be imported into Krona.", "platypus": "Platypus is a tool that efficiently and accurately calling genetic variants from next-generation DNA sequencin", "agat_convertgff2bed": "Takes a GFF3 file and converts to a bed12 file", "ganon_report": "Generate a ganon report file from the output of ganon classify", "bbmap_sendsketch": "Compares query sketches to reference sketches hosted on a remote server via the Internet."}}, "target": "kaiju_kaiju2krona", "target_idx": 0}
{"id": "field_constraint_sex_1_4", "category": "samplesheet_schema", "state": {"column": "sex", "purpose": "Biological sex in pedigree/trio clinical analysis"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'sex' (Biological sex in pedigree/trio clinical analysis).", "criteria": {"pattern: ^\\S+\\.gz$": null, "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": "resource_agat_convertgff2bed_4", "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_long": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "field_constraint_sample_1_11", "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, "pattern: ^\\S+$ (no whitespace, unique)": null, "type: integer": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 2}
{"id": "samplesheet_arch_dual_rnaseq_host_pathogen_4_2", "category": "samplesheet_schema", "state": {"assay": "Dual RNA-seq simultaneous host and pathogen transcriptomics", "first_step": "FASTQC"}, "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,host_fasta": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1,fastq_2,host,pathogen": null}}, "target": "sample,fastq_1,fastq_2,host,pathogen", "target_idx": 3}
{"id": "mod_cooler_dump_0", "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": {"cooler/dump": "Dump a cooler’s data to a text stream.", "gget/gget": "gget is a free, open-source command-line tool and Python package that enables efficient querying of genomic da", "sratools/fasterqdump": "Extract sequencing reads in FASTQ format from a given NCBI Sequence Read Archive (SRA).", "jvarkit/vcf2table": "Convert VCF to a user friendly table", "goat/taxonsearch": "Query metadata for any taxon across the tree of life."}}, "target": "cooler/dump", "target_idx": 0}
{"id": "mod_emboss_seqret_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Reads in one or more sequences, converts, filters, or transforms them and writes them out again (tools: emboss)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sylph_profile": null, "agat_convertspgff2gtf": null, "emboss_seqret": null, "agat_convertspgxf2gxf": null, "idr": null}}, "target": "emboss_seqret", "target_idx": 2}
{"id": "subworkflow_pkg_mafft_align_0", "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": {"Use nf-core subworkflow mafft_align": null, "Keep the modules in the main workflow": null, "Local subworkflow MAFFT_ALIGN": null, "Leave them out": null}}, "target": "Use nf-core subworkflow mafft_align", "target_idx": 0}
{"id": "samplesheet_arch_singlecell_parse_splitseq_6_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 are standard for Parse Biosciences Split-seq combinatorial barcoding input samplesheet?", "criteria": {"sample,subpool,fastq_1,fastq_2": null, "sample,well,plate": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,subpool,fastq_1,fastq_2", "target_idx": 0}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_7_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": "Which columns are standard for PacBio HiFi input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,bam": null, "sample,bam,bai": null}}, "target": "sample,bam", "target_idx": 2}
{"id": "qc_adapt_targeted_amplicon_1_38", "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": "resource_atlas_recal_2", "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_high": null, "process_single": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "local_subworkflow_irma_0_1", "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, "Local subworkflow IRMA": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Local subworkflow IRMA", "target_idx": 1}
{"id": "schema_std_methylarray_2_0", "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": {"sample_id,idat_red,idat_green,group": null, "sample,fastq_1,fastq_2,barcode": null, "sample_id,bam,vcf,library_id,lane": null, "id,raw_file": null}}, "target": "sample_id,idat_red,idat_green,group", "target_idx": 0}
{"id": "mod_agat_sqstatbasic_0", "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": {"custom/clustervisualization": "Generates UMAP and t-SNE visualizations colored by cluster", "agat/convertbed2gff": "Takes a bed12 file and converts to a GFF3 file", "gatk4/variantfiltration": "Filter variants", "agat/sqstatbasic": "Provides basic statistics in text format from a GFF/GTF annotation file", "abacas": "Contiguate draft genome assembly"}}, "target": "agat/sqstatbasic", "target_idx": 3}
{"id": "resource_bedtools_jaccard_4", "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_single": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_numorph_intensity_1", "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_resample": "performs resampling of light-sheet microscopy images", "numorph_3dunet": "3DUnet for cell nuclei quantification on 3D microscopy images of the numorph toolkit.", "cache_download_ensemblvep_snpeff": "downlad annotation cache for snpeff and ensemblvep", "crabs_insilicopcr": "CRABS extracts the amplicon region of the primer set by conducting an in silico PCR.", "numorph_intensity": "performs shading correction and intensity normalization between tile stacks"}}, "target": "numorph_intensity", "target_idx": 4}
{"id": "qc_adapt_pe_illumina_fastqc_2_11", "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": "noul_channel_operator_map_18", "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_qc_aggregate_1_48", "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_fastqscan_1", "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": {"diamond_blastx": "Queries a DIAMOND database using blastx mode", "ariba_run": "Query input FASTQs against Ariba formatted databases", "fastqscan": "FASTQ summary statistics in JSON format", "bamtofastq10x": "Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ATAC, Cell Ranger DNA, and Lon", "blobtk_depth": "Creates a bed file containing the depth of data at intervals of an aligned bam."}}, "target": "fastqscan", "target_idx": 2}
{"id": "mod_openms_psmfeatureextractor_0", "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": {"openms/idfilter": "Filters peptide/protein identification results by different criteria.", "openms/psmfeatureextractor": "Computes extra features for each input PSM for use with Percolator rescoring.", "glimpse/concordance": "Compute the r2 correlation between imputed dosages (in MAF bins) and highly-confident genotype calls from the ", "openms/idmerger": "Merges several idXML files into one idXML file.", "argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD)."}}, "target": "openms/psmfeatureextractor", "target_idx": 1}
{"id": "subworkflow_pkg_fasta_gxf_busco_plot_2", "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, "Use nf-core subworkflow fasta_gxf_busco_plot": null, "Leave them out": null, "Local subworkflow FASTA_GXF_BUSCO_PLOT": null}}, "target": "Use nf-core subworkflow fasta_gxf_busco_plot", "target_idx": 1}
{"id": "mod_fgumi_codec_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Call CODEC consensus reads from a UMI-grouped BAM with fgumi (tools: fgumi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pbtk_pbindex": "Minimalistic tool which creates an index file that enables random access into PacBio BAM files", "sambamba_markdup": "find and mark duplicate reads in BAM file", "fgumi_downsample": "Downsample a BAM by UMI family using streaming with fgumi", "fgbio_callmolecularconsensusreads": "Calls consensus sequences from reads with the same unique molecular tag.", "fgumi_codec": "Call CODEC consensus reads from a UMI-grouped BAM with fgumi"}}, "target": "fgumi_codec", "target_idx": 4}
{"id": "samplesheet_arch_scrna_10x_v3_1_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": "Which columns should the 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,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,expected_cells", "target_idx": 1}
{"id": "samplesheet_arch_chipseq_with_control_0_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: ChIP-seq with IP and input control design?", "criteria": {"sample,antibody,control": 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": "samplesheet_arch_chipseq_with_control_0_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": "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,antibody,control": null, "sample,antibody,control": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 1}
{"id": "qc_adapt_pacbio_hifi_2_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": "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_stringtie_stringtie_1", "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": {"oarfish_alignmentprojectionmode": "oarfish is a program for quantifying transcript-level expression from long-read sequencing technologies. Proje", "evigene_tr2aacds": "Uses evigene/scripts/prot/tr2aacds.pl to filter a transcript assembly", "cobrameta": "A tool to raise the quality of viral genomes assembled from short-read metagenomes via resolving and joining o", "stringtie_stringtie": "Transcript assembly and quantification for RNA-Se", "bakta_baktadbdownload": "Downloads BAKTA database from Zenodo"}}, "target": "stringtie_stringtie", "target_idx": 3}
{"id": "mod_fgbio_zipperbams_1", "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": {"gatk4_calculatecontamination": "Calculates the fraction of reads from cross-sample contamination based on summary tables from getpileupsummari", "fgbio_copyumifromreadname": "Copies the UMI at the end of a bam files read name to the RX tag.", "mashmap": "Mashmap is an approximate long read or contig mapper based on Jaccard similarity", "fgbio_filterconsensusreads": "Uses FGBIO FilterConsensusReads to filter consensus reads generated by CallMolecularConsensusReads or CallDupl", "fgbio_zipperbams": "FGBIO tool to zip together an unmapped and mapped BAM to transfer metadata into the output BAM"}}, "target": "fgbio_zipperbams", "target_idx": 4}
{"id": "mod_bigslice_bigslice_1", "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": {"picard_collectmultiplemetrics": "Collect multiple metrics from a BAM file", "bigslice_downloaddb": "Downloads and extracts the BiG-SLiCE HMM database (biosynthetic and sub Pfams)\nusing the bundled `download_big", "bismark_align": "Performs alignment of BS-Seq reads using bismark", "agat_spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "bigslice_bigslice": "A scalable tool for large-scale analysis of Biosynthetic Gene Clusters (BGCs).\nIt takes genome regions in GenB"}}, "target": "bigslice_bigslice", "target_idx": 4}
{"id": "intent_prepare_data_2", "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", "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": "prepare_data", "target_idx": 3}
{"id": "samplesheet_arch_vcf_annotation_pipeline_6_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 are standard for Downstream functional annotation of pre-called VCF files input samplesheet?", "criteria": {"sample,bam,bai": null, "sample,vcf,tbi": null, "sample,bed": null, "sample,vcf": null}}, "target": "sample,vcf,tbi", "target_idx": 1}
{"id": "mod_bcftools_pluginfilltags_1", "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_annotate": "Add or remove annotations.", "pairtools_flip": "Flip pairs to get an upper-triangular matrix", "bcftools_pluginfilltags": "Compute and fill various INFO tags", "bcftools_call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "roary": "Calculate pan-genome from annotated bacterial assemblies in GFF3 format"}}, "target": "bcftools_pluginfilltags", "target_idx": 2}
{"id": "samplesheet_arch_cutandrun_pe_4_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": "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,target,control": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 2}
{"id": "resource_bedtools_jaccard_5", "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_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "subworkflow_pkg_fastq_find_mirna_mirdeep2_0", "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": "resource_bedops_convert2bed_2", "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_long": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "noul_modifying_channel_meta_inside_bash_script_block_3", "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_gatk4_mergevcfs_1", "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": {"gatk4_baserecalibrator": "Generate recalibration table for Base Quality Score Recalibration (BQSR)", "coverm_genome": "Calculate read coverage per-genome", "gatk4_asereadcounter": "Calculates the allele-specific read counts for allele-specific expression analysis of RNAseq data", "cellranger_mkref": "Module to build the reference needed by the 10x Genomics Cell Ranger tool. Uses the cellranger mkref command.", "gatk4_mergevcfs": "Merges several vcf files"}}, "target": "gatk4_mergevcfs", "target_idx": 4}
{"id": "resource_bcftools_reheader_4", "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_long": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_deepcell_mesmer_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Deepcell/mesmer segmentation for whole-cell (tools: mesmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mcstaging_imc2mc": "Staging module for MCMICRO transforming Imaging Mass Cytometry .txt files to .tif files with OME-XML metadata.", "baysor_run": "Bayesian segmentation of spatial transcriptomics data.", "rundbcan_easysubstrate": "Substrate annotation module for the dbcan pipeline. This module is used to annotate carbohydrate-active enzyme", "deepcell_mesmer": "Deepcell/mesmer segmentation for whole-cell", "gunzip": "Compresses and decompresses files."}}, "target": "deepcell_mesmer", "target_idx": 3}
{"id": "resource_blast_blastn_0", "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_medium": null, "process_single": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_ampliseq_its_fungal_0_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": "Which columns should the input 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_channel_operator_map_14", "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_viral_ont_single_0_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 should the input samplesheet have for: Viral genome sequencing on Oxford Nanopore MinION / GridION?", "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": "mod_modkit_bedmethyltobigwig_0", "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": {"rtgtools/svdecompose": "The svdecompose tool of RTG tools. It is used to decompose structural variants to BNDs", "autocycler/trim": "Trim cluster assembly graphs to remove unsupported segments prior to resolution.", "happy/prepy": "Pre.py is a preprocessing tool made to preprocess VCF files for Hap.py", "autocycler/subsample": "Downsample long-read sequencing data to the requested coverage using Autocycler.", "modkit/bedmethyltobigwig": "Convert a bedMethyl file to bigWig format using modkit"}}, "target": "modkit/bedmethyltobigwig", "target_idx": 4}
{"id": "mod_sylph_sketchgenomes_1", "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": {"deeptools_plotprofile": "plots values produced by deeptools_computematrix as a profile plot", "fgumi_extract": "Extract unique molecular indices (UMIs) from FASTQ files and write an unaligned BAM file.", "falco": "Run falco on sequenced reads", "sylph_sketchgenomes": "Sylph profile command for taxonoming profiling of genomes", "expansionhunterdenovo_profile": "Compute genome-wide STR profile"}}, "target": "sylph_sketchgenomes", "target_idx": 3}
{"id": "mod_gatk4_analyzecovariates_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Evaluate and compare base quality score recalibration (BQSR) tables (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_pluginsplit": null, "parabricks_applybqsr": null, "gatk4spark_baserecalibrator": null, "gatk4_analyzecovariates": null, "custom_orfnormalise": null}}, "target": "gatk4_analyzecovariates", "target_idx": 3}
{"id": "mod_metaspace_download_1", "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": {"metaspace_download": "A module to download dataset results from the METASPACE platform and save them as CSV files, using a container", "metaspace_converter": "Export METASPACE datasets to AnnData and SpatialData objects", "csvtk_sort": "Sort  CSV (or TSV) tables", "metator_pipeline": "Metagenomic Tridimensional Organisation-based Reassembly - A set of scripts that streamlines the processing an", "csvtk_join": "Join two or more CSV (or TSV) tables by selected fields into a single table"}}, "target": "metaspace_download", "target_idx": 0}
{"id": "samplesheet_arch_viral_ont_single_3_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": "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": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "mod_hifiadapterfilt_downloaddb_1", "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": {"hificnv": null, "ribotricer_prepareorfs": null, "hifiasm": null, "gatk4_svcluster": null, "hifiadapterfilt_downloaddb": null}}, "target": "hifiadapterfilt_downloaddb", "target_idx": 4}
{"id": "mod_samtools_stats_0", "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": {"samtools/stats": "Produces comprehensive statistics from SAM/BAM/CRAM file", "msisensorpro/scan": "MSIsensor-pro evaluates Microsatellite Instability (MSI) for cancer patients with next generation sequencing d", "ampcombi": "A tool to parse and summarise results from antimicrobial peptides tools and present functional classification.", "agat/sqstatbasic": "Provides basic statistics in text format from a GFF/GTF annotation file", "bamstats/generalstats": "write your description here"}}, "target": "samtools/stats", "target_idx": 0}
{"id": "samplesheet_arch_cutandrun_pe_2_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 should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": 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": "mod_telomerehunter_1", "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": {"cnvkit_segment": "Infer discrete copy number segments from the given coverage table.", "atlas_pmd": "Estimate the post-mortem damage patterns of DNA", "bamclipper": "This module is used to clip primer sequences from your alignments.", "isoseq3_tag": "Extract UMI and cell barcodes", "telomerehunter": "In silico estimation of telomere content and composition from cancer genomes"}}, "target": "telomerehunter", "target_idx": 4}
{"id": "pipe_all101_mcmicro_0", "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": {"lsmquant": null, "mcmicro": null, "rnasplice": null, "magmap": null, "hicar": null}}, "target": "mcmicro", "target_idx": 1}
{"id": "samplesheet_arch_singlecell_parse_splitseq_1_1", "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 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": "schema_std_tfactivity_2_0", "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,condition,assay,peak_file,footprinting": null, "sample,fastq_1,fastq_2,fastq_barcode,expected_cells": null, "id,samplesheet,lane,flowcell,per_flowcell_manifest": null, "fasta,assembly,ncbi,gff,fastq": null}}, "target": "sample,condition,assay,peak_file,footprinting", "target_idx": 0}
{"id": "qc_adapt_qc_aggregate_2_36", "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": "resource_anota2seq_anota2seqrun_5", "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_single": null, "process_low": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_ngscheckmate_patterngenerator_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": {"rseqc_inferexperiment": "Infer strandedness from sequencing reads", "ngscheckmate_patterngenerator": "Determining whether sequencing data comes from the same individual by using SNP matching. This module generate", "ngscheckmate_fastq": "Determining whether sequencing data comes from the same individual by using SNP matching. This module generate", "ngscheckmate_vafncm": "Determining whether sequencing data comes from the same individual by using SNP matching. This module generate", "stringtie_merge": "Merges the annotation gtf file and the stringtie output gtf files"}}, "target": "ngscheckmate_patterngenerator", "target_idx": 1}
{"id": "mod_jvarkit_vcfpolyx_1", "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": {"geofetch": "geofetch is a command-line tool that downloads and organizes data and metadata from GEO and SRA", "gatk4_markduplicates": "This tool locates and tags duplicate reads in a BAM or SAM file, where duplicate reads are defined as originat", "jvarkit_vcfpolyx": "annotate VCF files for poly repeats", "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."}}, "target": "jvarkit_vcfpolyx", "target_idx": 2}
{"id": "pipe_all101_drop_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for drop. 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]", "hicar": "Pipeline for HiCAR data, a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chrom", "rnastructurome": "a bioinformatics pipeline for analysing chemical high-throughput RNA structure-probing data [dms, map, rna-structure]", "drop": "Pipeline to find aberrant events in RNA-Seq data, useful for diagnosis of rare disorders", "riboseq": "Pipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data.", "pathogensurveillance": "Surveillance of pathogens using population genomics and sequencing [biosurveillance, pathogen-identification]", "proteinfold": "Protein 3D structure prediction pipeline [alphafold2, colabfold, esmfold]", "proteinannotator": "Generation of sequence-level annotations for amino acid sequences [annotation, proteomics]", "createtaxdb": "Parallelised and automated construction of metagenomic classifier databases of different tools [database, database-build"}}, "target": "drop", "target_idx": 4}
{"id": "resource_bbmap_align_1", "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_single": null, "process_long": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "schema_std_mag_0_0", "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,fastq_2,group": null, "seeds,network,perturbed_networks": null, "fastq_1,fastq_2,batch,amp_batches,seq_batches": null}}, "target": "sample,run,group,short_reads_1,short_reads_2", "target_idx": 0}
{"id": "subworkflow_pkg_bam_impute_quilt2_0", "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": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow bam_impute_quilt2": null, "Leave them out": null, "Local subworkflow BAM_IMPUTE_QUILT2": null}}, "target": "Use nf-core subworkflow bam_impute_quilt2", "target_idx": 1}
{"id": "pipe_all101_pixelator_0", "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": {"references": null, "pixelator": null, "seqinspector": null, "longraredisease": null, "demultiplex": null, "rnavar": null, "epitopeprediction": null, "demo": null, "nanoseq": null, "proteinfold": null}}, "target": "pixelator", "target_idx": 1}
{"id": "mod_echtvar_anno_1", "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": {"echtvar_encode": "Make (encode) a new echtvar file from decomposed vcf", "minimac4_impute": "Imputation of genotypes using a reference panel", "bcftools_annotate": "Add or remove annotations.", "echtvar_anno": "Annotate a decomposed (and normalized) VCF with an echtvar file", "deeptools_computematrix": "calculates scores per genome regions for other deeptools plotting utilities"}}, "target": "echtvar_anno", "target_idx": 3}
{"id": "samplesheet_arch_viral_amplicon_artic_2_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 should the input samplesheet have?", "criteria": {"sample,bam": 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_plink2_pca_1", "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": {"fgumi_codec": "Call CODEC consensus reads from a UMI-grouped BAM with fgumi", "plink2_remove": "Remove samples from a plink2 dataset", "plink2_filter": "Filters plink bfiles or pfiles with filters such as maf or var", "xengsort_index": "Fast lightweight accurate xenograft sorting", "plink2_pca": "Perform PCA analysis using PLINK"}}, "target": "plink2_pca", "target_idx": 4}
{"id": "mod_glimpse2_chunk_1", "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": {"vcf_impute_glimpse": "Subworkflow to impute VCF files using GLIMPSE V1 software. The subworkflow\ntakes VCF files, phased reference p", "glimpse2_chunk": "Defines chunks where to run imputation", "bamtools_split": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "getorganelle_fromreads": "Assembles organelle genomes from genomic data", "pairix": "a tool for indexing and querying on a block-compressed text file\ncontaining pairs of genomic coordinates"}}, "target": "glimpse2_chunk", "target_idx": 1}
{"id": "samplesheet_arch_singlecell_parse_splitseq_5_0", "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": "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,subpool,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,subpool,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_autocycler_combine_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge resolved cluster assemblies into final consensus outputs with Autocycler. (tools: autocycler)?", "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.", "autocycler/subsample": "Downsample long-read sequencing data to the requested coverage using Autocycler.", "crisprcleanr/normalize": "remove false positives of functional crispr genomics due to CNVs", "fasta_consensus_autocycler": "Generate consensus assemblies and assembly graphs from grouped contig FASTA files using autocycler", "annotsv/annotsv": "Annotation and Ranking of Structural Variation"}}, "target": "autocycler/combine", "target_idx": 0}
{"id": "qc_adapt_bulk_multiqc_1_21", "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": "schema_std_genephylomodeler_0_1", "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": {"id,samplesheet,lane,flowcell,per_flowcell_manifest": null, "sample,alleles,mhc_class,filename": null, "gene_name,alignment,tree,suite,tool": null, "ID,R1,R2,LongFastQ,Fast5": null}}, "target": "gene_name,alignment,tree,suite,tool", "target_idx": 2}
{"id": "samplesheet_arch_smartseq_plate_based_2_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 should the input samplesheet have?", "criteria": {"plate,well,sample,fastq_1,fastq_2": null, "sample,well,fastq": null, "sample,fastq_1,fastq_2": null, "sample,matrix": null}}, "target": "plate,well,sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_genomescope2_0", "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": {"percolator": null, "bedtools/multiinter": null, "genomescope2": null, "vcfpgloader/load": null, "numorph/3dunet": null}}, "target": "genomescope2", "target_idx": 2}
{"id": "samplesheet_arch_bulk_wgs_pe_5_4", "category": "samplesheet_schema", "state": {"assay": "Standard Paired-end Whole Genome Sequencing (WGS)", "first_step": "FASTQC"}, "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": null, "sample,fastq_1,fastq_2,group": 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": "samplesheet_arch_amplicon_16s_paired_5_4", "category": "samplesheet_schema", "state": {"assay": "16S rRNA / ITS microbiome amplicon profiling", "first_step": "FASTQC"}, "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,fasta": 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": "mod_huggingface_download_1", "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": {"aria2": null, "huggingface_download": null, "bigslice_downloaddb": null, "minimac4_impute": null, "disambiguate": null}}, "target": "huggingface_download", "target_idx": 1}
{"id": "qc_adapt_qc_aggregate_2_41", "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_orfipy_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: orfipy is a tool written in python/cython to extract ORFs in an extremely and fast and flexible manner. (tools: orfipy)?", "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.", "velocyto": "Velocyto is a library for the analysis of RNA velocity. velocyto.py CLI use\n`Path(resolve_path=True)` and brea", "td2_longorfs": "TD2 identifies candidate coding regions within transcript sequences, such as those generated by de novo RNA-Se", "samtools_fastq": "Converts a SAM/BAM/CRAM file to FASTQ", "td2_predict": "TD2 identifies candidate coding regions within transcript sequences, such as those generated by de novo RNA-Se"}}, "target": "orfipy", "target_idx": 0}
{"id": "samplesheet_arch_epigenomics_hic_2_4", "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 input samplesheet have?", "criteria": {"sample,bam": 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": "resource_angsd_realsfs_2", "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_low": null, "process_single": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "schema_std_methylong_2_1", "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,fastq_1,fastq_2,replicate,control": null, "sample,group,path,ref,method": null, "sample,fasta,protein,gbk,gff": null, "patient,vcf,tbi,dataset,tumour_sample": null}}, "target": "sample,group,path,ref,method", "target_idx": 1}
{"id": "schema_std_phaseimpute_0_0", "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_id,name,description,path,path_2": null, "sample,fastq_1,fastq_2,antibody,control": null, "id,fasta,reference,optional_data,template": null}}, "target": "sample,tools,file,index", "target_idx": 0}
{"id": "mod_bcftools_stats_0", "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": {"bcftools/stats": "Generates stats from VCF files", "bcftools/concat": "Concatenate VCF files", "atlas/call": "generate VCF file from a BAM file using various calling methods", "utils_nfvalidation_plugin": "Use nf-validation to initiate and validate a pipeline", "kraken2/buildstandard": "Downloads and builds Kraken2 standard database"}}, "target": "bcftools/stats", "target_idx": 0}
{"id": "resource_agat_spfilterbyorfsize_3", "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_low": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_illumina_novaseq_1_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": "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": "field_constraint_strandedness_2_2", "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": "mod_deacon_filter_1", "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": {"biscuit_bsconv": "Summarize and/or filter reads based on bisulfite conversion rate", "bedtools_maskfasta": "masks sequences in a FASTA file based on intervals defined in a feature file.", "deacon_filter": "Filter DNA sequences using index of reference genome", "sourmash_sketch": "Create a signature (a group of FracMinHash sketches) of a sequence using sourmash", "bbmap_filterbyname": "Filter out sequences by sequence header name(s)"}}, "target": "deacon_filter", "target_idx": 2}
{"id": "qc_adapt_qc_aggregate_2_22", "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_stadeniolib_scramble_1", "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": {"samtools_faidx": "Index FASTA file, and optionally generate a file of chromosome sizes", "bwa_samse": "Convert bwa SA coordinate file to SAM format", "spring_decompress": "Fast, efficient, lossless decompression of FASTQ files.", "stadeniolib_scramble": "Advanced sequence file format conversions", "bwa_mem": "Performs fastq alignment to a fasta reference using BWA"}}, "target": "stadeniolib_scramble", "target_idx": 3}
{"id": "mod_bam_subsampledepth_samtools_1", "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": {"trycycler_subsample": "Subsample a long-read sequencing fastq file for multiple assemblies", "bam_subsampledepth_samtools": "Subsample a BAM/CRAM/SAM file using samtools to a given mean depth.\n\"region\", \"subsample_fraction\", \"mean_dept", "merqury_hapmers": "A script to generate hap-mer dbs for trios", "variantbam": "Filtering, downsampling and profiling alignments in BAM/CRAM formats", "fq_subsample": "fq subsample outputs a subset of records from single or paired FASTQ files. This requires a seed (--seed) to b"}}, "target": "bam_subsampledepth_samtools", "target_idx": 1}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_2_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 should the input samplesheet have?", "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": "field_constraint_expected_cells_2_5", "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, "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": "qc_adapt_pe_illumina_fastqc_0_42", "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": "samplesheet_arch_taxprofiler_shotgun_3_1", "category": "samplesheet_schema", "state": {"assay": "Multi-taxonomic profiling of complex metagenomic shotgun reads", "first_step": "FASTQC", "template": "nf-core/taxprofiler"}, "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,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_taxpasta_standardise_1", "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": {"taxpasta_standardise": "Standardise the output of a wide range of taxonomic profilers", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "stainwarpy_transformsegmask": "Transform segmentation mask of multiplexed or H&E stained tissue images using stainwarpy", "biomformat_convert": "Convert biom table to different format.\nConversion between text tab-delimited, BIOM-v1 (JSON), and BIOM-v2 (HD", "samtools_sormadup": "Collate/Fixmate/Sort/Markdup SAM/BAM/CRAM file"}}, "target": "taxpasta_standardise", "target_idx": 0}
{"id": "noul_deprecated_file_output_syntax_7", "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_cellranger_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 tool. Uses the cellranger mkgtf command. (tools: cellranger)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"autocycler/trim": null, "seqkit/fx2tab": null, "cellranger/mkgtf": null, "bowtie/build": null, "bowtie/align": null}}, "target": "cellranger/mkgtf", "target_idx": 2}
{"id": "samplesheet_arch_cancer_somatic_bam_5_2", "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": "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, "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_status_0_9", "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_named_process_output_emits_11", "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_assemblyscan_5", "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_long": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_kled_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: An ultra-fast and sensitive structural variant detection tool for long-read sequencing data. (tools: kled)?", "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", "kled": "An ultra-fast and sensitive structural variant detection tool for long-read sequencing data.", "regenie/splitl0": "Split REGENIE step 1 level-0 ridge-regression blocks into parallel jobs", "agat/spfilterfeaturefromkilllist": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID", "manta/tumoronly": "Manta calls structural variants (SVs) and indels from mapped paired-end sequencing reads. It is optimized for "}}, "target": "kled", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_1_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": "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_ont_ultra_long_0_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": "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_emboss_seqret_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Reads in one or more sequences, converts, filters, or transforms them and writes them out again (tools: emboss)?", "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", "gcta/bivariatereml": "Run bivariate REML analysis with a single dense GRM", "emboss/seqret": "Reads in one or more sequences, converts, filters, or transforms them and writes them out again", "graphmap2/index": "A versatile pairwise aligner for genomic and spliced nucleotide sequences", "agat/convertspgff2tsv": "Converts a GFF/GTF file into a TSV file"}}, "target": "emboss/seqret", "target_idx": 2}
{"id": "mod_csvtk_join_0", "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": {"goat/taxonsearch": "Query metadata for any taxon across the tree of life.", "csvtk/join": "Join two or more CSV (or TSV) tables by selected fields into a single table", "emboss/revseq": "the revseq program from emboss reverse complements a nucleotide sequence", "snpsift/split": "Splits/Joins VCF(s) file into chromosomes", "annotsv/annotsv": "Annotation and Ranking of Structural Variation"}}, "target": "csvtk/join", "target_idx": 1}
{"id": "mod_goleft_indexsplit_1", "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": {"pilon": "Automatically improve draft assemblies and find variation among strains, including large event detection", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files.", "goleft_indexsplit": "Quickly generate evenly sized (by amount of data) regions across a number of bam/cram files", "gapseq_medium": "Predict growth medium from a draft model and pathway predictions", "atlas_pmd": "Estimate the post-mortem damage patterns of DNA"}}, "target": "goleft_indexsplit", "target_idx": 2}
{"id": "mod_plink2_extract_0", "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/pmerge": "Merge a second PLINK 2 fileset into the first and write a new combined PLINK 2 fileset", "plink2/remove": "Remove samples from a plink2 dataset", "pharmcat/vcfpreprocessor": "The PharmCAT VCF Preprocessor is a script that can pre-process VCF files for PharmCAT to make sure the VCF fil", "plink2/extract": "Subset plink pfiles with a text file of variant identifiers", "simpleaf/quant": "simpleaf is a program to simplify and customize the running and configuration of single-cell processing with a"}}, "target": "plink2/extract", "target_idx": 3}
{"id": "pipe_all101_proteinannotator_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": {"proteinannotator": "Generation of sequence-level annotations for amino acid sequences [annotation, proteomics]", "pathogensurveillance": "Surveillance of pathogens using population genomics and sequencing [biosurveillance, pathogen-identification]", "crisprseq": "A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments u", "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"}}, "target": "proteinannotator", "target_idx": 0}
{"id": "samplesheet_arch_cancer_somatic_tn_5_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": "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, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_picard_createsequencedictionary_1", "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": {"picard_createsequencedictionary": "Creates a sequence dictionary for a reference sequence.", "trtools_dumpstr": "DumpSTR filters VCF files with TR genotypes, performing call-level and locus-level filtering, and outputs a fi", "fq_generate": "fq generate is a FASTQ file pair generator. It creates two reads, formatting names as described by Illumina. W", "agat_spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "khmer_normalizebymedian": "Module that calls normalize-by-median.py from khmer. The module can take a mix of paired end (interleaved) and"}}, "target": "picard_createsequencedictionary", "target_idx": 0}
{"id": "samplesheet_arch_pacbio_hifi_wgs_3_2", "category": "samplesheet_schema", "state": {"technology": "Long-Read Sequencing", "workflow_entry": "HIFIADAPTERFILT", "library_inputs": "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,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "subworkflow_pkg_fastq_ngscheckmate_1", "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": {"Local subworkflow FASTQ_NGSCHECKMATE": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow fastq_ngscheckmate": null}}, "target": "Use nf-core subworkflow fastq_ngscheckmate", "target_idx": 3}
{"id": "samplesheet_arch_bulk_wgs_pe_6_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 are standard for Standard Paired-end Whole Genome Sequencing (WGS) input samplesheet?", "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": "subworkflow_pkg_fasta_gtf_bam_rpbp_2", "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, "Use nf-core subworkflow fasta_gtf_bam_rpbp": null, "Keep the modules in the main workflow": null, "Local subworkflow FASTA_GTF_BAM_RPBP": null}}, "target": "Use nf-core subworkflow fasta_gtf_bam_rpbp", "target_idx": 1}
{"id": "resource_affy_justrma_4", "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_long": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_amplicon_16s_paired_4_5", "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": "What samplesheet columns are expected when inputs are: Demultiplexed paired-end 250bp or 300bp Illumina amplicon FASTQs?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,otu_table": null, "sample,fasta": null, "sample,primer_fwd,primer_rev": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "noul_named_output_channel_access_10", "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_rgi_bwt_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": {"abritamr/run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes", "abricate/run": "Screen assemblies for antimicrobial resistance against multiple databases", "rgi/bwt": "Predict antibiotic resistance from protein or nucleotide data", "fastq_fastqc_umitools_trimgalore": "Read QC, UMI extraction and trimming", "bam_sort_stats_samtools": "Sort SAM/BAM/CRAM file"}}, "target": "rgi/bwt", "target_idx": 2}
{"id": "noul_executor_support_14", "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_bulk_rnaseq_se_0_3", "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 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,fastq_1": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 0}
{"id": "samplesheet_arch_ampliseq_its_fungal_6_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 are standard for Fungal ITS1/ITS2 marker gene amplicon surveillance input samplesheet?", "criteria": {"sample,unite_fasta": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,primer_its1,primer_its2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "samplesheet_arch_ancient_dna_eager_0_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": "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,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": "resource_biomformat_convert_3", "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_high": null, "process_low": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "qc_adapt_qc_aggregate_0_22", "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_default_empty_channel_behavior_15", "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_merfin_hist_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compare k-mer frequency in reads and assembly to devise the metrics K* and QV* (tools: merfin)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"merfin/hist": null, "plink2/pca": null, "cafe": null, "abricate/run": null, "abacas": null}}, "target": "merfin/hist", "target_idx": 0}
{"id": "pipe_all101_riboseq_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Pipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data.. ?", "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-", "lsmquant": "A pipeline for processing and analysis of light-sheet microscopy images. [3dunet, image-analysis, image-processing]", "nanoseq": "Nanopore demultiplexing, QC and alignment pipeline [alignment, demultiplexing, nanopore]", "callingcards": "A pipeline for processing calling cards data", "proteinannotator": "Generation of sequence-level annotations for amino acid sequences [annotation, proteomics]", "spatialaxe": "A bioinformatics best-practice processing and quality control pipeline for Xenium and Artera data [10x-genomics, atera, ", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline [atac-seq, chromatin-accessibiity]", "riboseq": "Pipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data."}}, "target": "riboseq", "target_idx": 7}
{"id": "mod_plink_hwe_1", "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": {"ucsc_bedgraphtobigwig": "Convert a bedGraph file to bigWig format.", "seqkit_split2": "Split single or paired-end fastq.gz files", "plink_hwe": "Generate Hardy-Weinberg statistics for provided input", "kled": "An ultra-fast and sensitive structural variant detection tool for long-read sequencing data.", "ngsbits_samplegender": "Determines the gender of a sample from the BAM/CRAM file."}}, "target": "plink_hwe", "target_idx": 2}
{"id": "samplesheet_arch_bulk_small_rna_2_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 should the input samplesheet have?", "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": "mod_telseq_1", "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": {"seacr_callpeak": "Call peaks using SEACR on sequenced reads in bedgraph format", "telseq": "Telseq: a software for calculating telomere length", "ascat": "copy number profiles of tumour cells.", "saltshaker_classify": "mtDNA deletion and duplication classification downstream of mitosalt", "bamclipper": "This module is used to clip primer sequences from your alignments."}}, "target": "telseq", "target_idx": 1}
{"id": "mod_maxquant_lfq_0", "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": {"survivor/filter": null, "biobambam/bamsormadup": null, "seacr/callpeak": null, "crisprcleanr/normalize": null, "maxquant/lfq": null}}, "target": "maxquant/lfq", "target_idx": 4}
{"id": "samplesheet_arch_bulk_rnaseq_pe_6_3", "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 are standard for Paired-end Illumina RNA-seq with strandedness input samplesheet?", "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": "mod_gatk4_calculatecontamination_1", "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": {"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", "gatk4_analyzecovariates": "Evaluate and compare base quality score recalibration (BQSR) tables", "sambamba_depth": "Outputs a coverage file from bam files", "utils_nfschema_plugin": "Run nf-schema to validate parameters and create a summary of changed parameters"}}, "target": "gatk4_calculatecontamination", "target_idx": 1}
{"id": "mod_myloasm_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Myloasm is a de novo metagenome assembler for long-read sequencing data.\nIt takes sequencing reads and outputs polished contigs in a single command. (tools: myloasm)?", "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", "tidk/search": "Searches a genome for a telomere string such as TTAGGG", "myloasm": "Myloasm is a de novo metagenome assembler for long-read sequencing data.\nIt takes sequencing reads and outputs", "semibin/singleeasybin": "metagenomic binning with self-supervised learning", "abacas": "Contiguate draft genome assembly"}}, "target": "myloasm", "target_idx": 2}
{"id": "samplesheet_arch_bulk_rnaseq_pe_5_5", "category": "samplesheet_schema", "state": {"assay": "Paired-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: Paired-end Illumina RNA-seq with strandedness.", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,group": 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": "local_subworkflow_prepilluminareads_2_0", "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, "Leave them out": null, "Local subworkflow PREPILLUMINAREADS": null}}, "target": "Local subworkflow PREPILLUMINAREADS", "target_idx": 3}
{"id": "noul_file_pairing_in_channel_tuples_23", "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": "pipe_all101_raredisease_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for diagnostics. 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]", "raredisease": "Call and score variants from WGS/WES of rare disease patients. [diagnostics, rare-disease, snv]", "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]", "circdna": "Pipeline for the identification of extrachromosomal circular DNA (ecDNA) from Circle-seq, WGS, and ATAC-seq data that we", "proteogenomicsdb": "The ProteoGenomics database generation workflow creates different protein databases for ProteoGenomics data analysis. [c", "kmermaid": " k-mer similarity analysis pipeline [k-mer, kmer, kmer-counting]", "hlatyping": "Precision HLA typing from next-generation sequencing data [dna, hla, hla-typing]"}}, "target": "raredisease", "target_idx": 1}
{"id": "mod_fgbio_copyumifromreadname_1", "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": {"fgbio_copyumifromreadname": "Copies the UMI at the end of a bam files read name to the RX tag.", "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", "gawk": "If you are like many computer users, you would frequently like to make changes in various text files\nwherever ", "kaiju_mkfmi": "Make Kaiju FMI-index file from a protein FASTA file"}}, "target": "fgbio_copyumifromreadname", "target_idx": 0}
{"id": "resource_blobtk_depth_5", "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_high": null, "process_long": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "noul_subworkflow_structural_blocks_8", "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_methylseq_bisulfite_5_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": "In Nextflow pipeline nf-core/methylseq, determine the input samplesheet column structure for: Whole-Genome Bisulfite Sequencing (WGBS / EM-seq).", "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_any2fasta_0", "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_high": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "field_constraint_fastq_2_1_9", "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, "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_cram_indexed_1_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": "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,cram,crai": null, "sample,bam,bai": null}}, "target": "sample,cram,crai", "target_idx": 2}
{"id": "qc_adapt_singlecell_multiqc_2_22", "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_deeptools_computematrix_1", "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": {"cdhit_cdhit": "Cluster protein sequences using sequence similarity", "deeptools_computematrix": "calculates scores per genome regions for other deeptools plotting utilities", "custom_dumpsoftwareversions": "Custom module used to dump software versions within the nf-core pipeline template", "abacas": "Contiguate draft genome assembly", "agat_convertbed2gff": "Takes a bed12 file and converts to a GFF3 file"}}, "target": "deeptools_computematrix", "target_idx": 1}
{"id": "mod_smoove_call_1", "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": {"smoove_call": "smoove simplifies and speeds calling and genotyping SVs for short reads. It also improves specificity by remov", "caddsv_run": "Score structural variants with CADD-SV.", "genmap_index": "create index file for genmap", "genomescope2": "Estimate genome heterozygosity, repeat content, and size from sequencing reads using a kmer-based statistical ", "gatk4_collectsvevidence": "Gathers paired-end and split read evidence files for use in the GATK-SV pipeline. Output files are a file cont"}}, "target": "smoove_call", "target_idx": 0}
{"id": "mod_bbmap_index_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode. (tools: bbmap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bismark/coverage2cytosine": null, "bismark/deduplicate": null, "ucsc/wigtobigwig": null, "trust4": null, "bbmap/index": null}}, "target": "bbmap/index", "target_idx": 4}
{"id": "samplesheet_arch_prealigned_bam_indexed_6_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 are standard for Pre-aligned BAM variant calling pipeline input samplesheet?", "criteria": {"sample,bam": null, "sample,bam,bai": null, "sample,fastq_1": null, "sample,vcf": null}}, "target": "sample,bam,bai", "target_idx": 1}
{"id": "noul_named_process_output_emits_23", "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": "subworkflow_pkg_fasta_index_bismark_bwameth_0", "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, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Use nf-core subworkflow fasta_index_bismark_bwameth", "target_idx": 0}
{"id": "mod_cellrangerarc_mkfastq_0", "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": {"bbmap/align": "Align short or PacBio reads to a reference genome using BBMap", "bbmap/bbsplit": "Split sequencing reads by mapping them to multiple references simultaneously", "manta/germline": "Manta calls structural variants (SVs) and indels from mapped paired-end sequencing reads. It is optimized for ", "cellrangerarc/mkfastq": "Module to create fastqs needed by the 10x Genomics Cell Ranger Arc tool. Uses the cellranger-arc mkfastq comma", "minibwa/index": "Create a minibwa index for a reference genome"}}, "target": "cellrangerarc/mkfastq", "target_idx": 3}
{"id": "mod_trimmomatic_0", "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": {"fasta_index_methylseq": "Generate index files from reference fasta for bismark, bwameth and bwamem aligners", "chelae/trim": "Adapter and quality trimming of short-read FASTQ data using chelae.", "chopper": "Filter and trim long read data.", "transdecoder/longorf": "TransDecoder identifies candidate coding regions within transcript sequences. it is used to build gff file.", "trimmomatic": "Performs quality and adapter trimming on paired end and single end reads"}}, "target": "trimmomatic", "target_idx": 4}
{"id": "field_constraint_fastq_1_3_8", "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": "mod_bcftools_pluginvcf2table_1", "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_annotate": "Add or remove annotations.", "hmmer_hmmsearch": "search profile(s) against a sequence database", "hisat2_extractsplicesites": "Extracts splicing sites from a gtf files", "bcftools_index": "Index VCF tools", "bcftools_pluginvcf2table": "Converts VCF/BCF files into a tab-delimited table using the bcftools +vcf2table plugin.\nEach variant is output"}}, "target": "bcftools_pluginvcf2table", "target_idx": 4}
{"id": "resource_arcashla_extract_3", "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_low": null, "process_single": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_shigatyper_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Determine Shigella serotype from Illumina or Oxford Nanopore reads (tools: shigatyper)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"shigatyper": "Determine Shigella serotype from Illumina or Oxford Nanopore reads", "fastq_align_chromap": "Align high throughput chromatin profiles using Chromap, updating readgroups if neccessary and then sort with s", "adapterremovalfixprefix": "Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with", "fastp": "Perform adapter/quality trimming on sequencing reads", "ariba/run": "Query input FASTQs against Ariba formatted databases"}}, "target": "shigatyper", "target_idx": 0}
{"id": "schema_std_references_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/references", "description": "nf-core/references is a bioinformatics pipeline that build references, for multiple use cases", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/references?", "criteria": {"sample,fastq_1,fastq_2,batch,condition": null, "sample,fastq_1,fastq_2,sampleID,forwardReads": null, "vcf,fasta,genome,site,source": null, "sample,bam,bai,cram,crai": null}}, "target": "vcf,fasta,genome,site,source", "target_idx": 2}
{"id": "local_subworkflow_prepontreads_1_2", "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_riboseq_profiling_3_0", "category": "samplesheet_schema", "state": {"assay": "Ribosome profiling (Ribo-seq) footprint sequencing", "first_step": "FASTQC"}, "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,fastq_1,fastq_2": null, "sample,cdna_fasta": null, "sample,fastq_1,strandedness": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 3}
{"id": "subworkflow_pkg_fastq_create_umi_consensus_fgbio_0", "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, "Use nf-core subworkflow fastq_create_umi_consensus_fgbio": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fastq_create_umi_consensus_fgbio", "target_idx": 1}
{"id": "samplesheet_arch_amplicon_16s_paired_4_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": "What samplesheet columns are expected when inputs are: Demultiplexed paired-end 250bp or 300bp Illumina amplicon FASTQs?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,otu_table": null, "sample,fastq_1": null, "sample,primer_fwd,primer_rev": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "samplesheet_arch_riboseq_profiling_5_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": "In Nextflow pipeline nf-core/riboseq, determine the input samplesheet column structure for: Ribosome profiling (Ribo-seq) footprint sequencing.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,strandedness": null, "sample,cdna_fasta": null, "sample,vcf": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 1}
{"id": "noul_deprecated_dsl1_set_keyword_21", "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_viralrecon_0", "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": {"mag": null, "sarek": null, "viralrecon": null, "coproid": null, "variantbenchmarking": null}}, "target": "viralrecon", "target_idx": 2}
{"id": "mod_custom_catadditionalfasta_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Custom module to Add a new fasta file to an old one and update an associated GTF (tools: custom)?", "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.", "amrfinderplus_update": "Identify antimicrobial resistance in gene or protein sequences", "bedtools_closest": "For each feature in A, finds the closest feature (upstream or downstream) in B.", "custom_catadditionalfasta": "Custom module to Add a new fasta file to an old one and update an associated GTF", "gstama_polyacleanup": "Helper script, remove remaining polyA sequences from Full Length Non Chimeric reads (Pacbio isoseq3)"}}, "target": "custom_catadditionalfasta", "target_idx": 3}
{"id": "mod_openms_peptideindexer_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Refreshes the protein references for all peptide hits. (tools: openms)?", "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.", "sparsesignatures": "mutational signature deconvolution of cancer cells", "openms/peptideindexer": "Refreshes the protein references for all peptide hits.", "openms/psmfeatureextractor": "Computes extra features for each input PSM for use with Percolator rescoring.", "slamdunk/all": "Complete SLAMseq analysis pipeline including read mapping, filtering, SNP calling, and quantification"}}, "target": "openms/peptideindexer", "target_idx": 2}
{"id": "field_constraint_sample_1_0", "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": "samplesheet_arch_bacterial_hybrid_assembly_1_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": "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,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_targeted_amplicon_1_41", "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_csvtk_sort_0", "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": {"crisprcleanr/normalize": null, "csvtk/sort": null, "biobambam/bamsormadup": null, "pharmcat/reporter": null, "pyclonevi": null}}, "target": "csvtk/sort", "target_idx": 1}
{"id": "mod_lofreq_callparallel_0", "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": {"spades": null, "bcftools/consensus": null, "lofreq/callparallel": null, "whatshap/phase": null, "aardvark/merge": null}}, "target": "lofreq/callparallel", "target_idx": 2}
{"id": "field_constraint_phenotype_3_9", "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, "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": "noul_file_pairing_in_channel_tuples_14", "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_skani_dist_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Simple ANI calculation between reference and query genomes. (tools: skani)?", "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.", "sentieon_tnhaplotyper2": "Tnhaplotyper2 performs somatic variant calling on the tumor-normal matched pairs.", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "sratools_fasterqdump": "Extract sequencing reads in FASTQ format from a given NCBI Sequence Read Archive (SRA).", "argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD)."}}, "target": "skani_dist", "target_idx": 0}
{"id": "samplesheet_arch_atacseq_replicates_0_2", "category": "samplesheet_schema", "state": {"assay": "ATAC-seq chromatin accessibility with biological replicates", "first_step": "FASTQC"}, "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": null, "sample,bed": null, "sample,fastq_1,fastq_2,replicate": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 3}
{"id": "field_constraint_bai_1_0", "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$": null, "pattern: ^\\S+\\.crai$": null, "type: boolean": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 1}
{"id": "pipe_all101_circdna_5", "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": {"drugresponseeval": "Pipeline for testing drug response prediction models in a statistically and biologically sound way. [cell-lines, cross-v", "proteinfold": "Protein 3D structure prediction pipeline [alphafold2, colabfold, esmfold]", "genomeqc": "Compare the quality of multiple genomes, along with their annotations. [genome-assembly-evaluation, genomics, phylogenet", "cutandrun": "Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak callin", "variantbenchmarking": "Pipeline to evaluate and validate the accuracy of variant calling methods in genomic research [benchmark, small-variants", "scnanoseq": "Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics [10xgenomics, long-read-sequencing, n", "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"}}, "target": "circdna", "target_idx": 7}
{"id": "resource_bcftools_view_1", "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_low": null, "process_medium": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_vcftools_0", "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": {"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.", "vcftools": "A set of tools written in Perl and C++ for working with VCF files", "snapaligner/align": "Performs fastq alignment to a fasta reference using SNAP", "any2fasta": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input "}}, "target": "vcftools", "target_idx": 2}
{"id": "mod_drep_compare_0", "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/dereplicate": "Dereplicates a genome  set by identifying highly similar genomes and choose the best representative genome", "antismash/antismashdownloaddatabases": "antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynt", "agat/convertspgff2gtf": "Converts a GFF/GTF file into a proper GTF file", "drep/compare": "Performs rapid genome comparisons for a group of genomes and visualize their relatedness", "gt/ltrharvest": "Predicts LTR retrotransposons using GenomeTools gt-ltrharvest utility"}}, "target": "drep/compare", "target_idx": 3}
{"id": "schema_std_alleleexpression_1_0", "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": {"RNA_ID,RNA_BAM_FILE,RNA_BAI_FILE,DNA_ID,DNA_VCF_FILE": null, "id,taxid,fasta_dna,fasta_aa": null, "sample,fastq_1,fastq_2,vcf": null, "sample,fasta,existing_hmms_to_update,existing_msas_to_update": null}}, "target": "sample,fastq_1,fastq_2,vcf", "target_idx": 2}
{"id": "resource_autocycler_cluster_2", "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_low": null, "process_high": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_miranda_1", "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_stats": "mirtop gff gets the number of isomiRs and miRNAs annotated in the GFF file by isomiR category.", "mirdeep2_mirdeep2": "miRDeep2 is a tool for identifying known and novel miRNAs in deep sequencing data by analyzing sequenced RNAs.", "survivor_bedpetovcf": "Converts a bedpe file to a VCF file (beta version)", "miranda": "miRanda is an algorithm for finding genomic targets for microRNAs", "fgumi_correct": "Correct UMIs in a BAM file to a fixed set of known UMIs with fgumi"}}, "target": "miranda", "target_idx": 3}
{"id": "samplesheet_arch_proteomics_dia_1_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": "Which columns should the samplesheet have for Data-Independent Acquisition (DIA) quantitative mass spectrometry?", "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": "intent_prepare_data_15", "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, "prepare_data": null, "ask_question": null}}, "target": "prepare_data", "target_idx": 2}
{"id": "mod_leviosam2_lift_0", "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": {"leviosam2/lift": "Converting aligned short and long reads records from one reference to another", "biscuit/qc": "Perform basic quality control on a BAM file generated with Biscuit", "tinc": "TINC is a package to determine the contamination of tumour DNA in a matched normal sample. The approach uses e", "gt/gff3": "GenomeTools gt-gff3 utility to parse, possibly transform, and output GFF3 files", "bbmap/index": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode."}}, "target": "leviosam2/lift", "target_idx": 0}
{"id": "schema_std_diseasemodulediscovery_1_0", "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": {"id,fasta": null, "sample,fastq_1,fastq_2,batch,condition": null, "seeds,network,perturbed_networks": null, "vcf,fasta,genome,site,source": null}}, "target": "seeds,network,perturbed_networks", "target_idx": 2}
{"id": "mod_gatk4_createsomaticpanelofnormals_0", "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": {"ribotish/quality": "Quality control of riboseq bam data", "vsearch/sintax": "Taxonomic classification using the sintax algorithm.", "gatk4/asereadcounter": "Calculates the allele-specific read counts for allele-specific expression analysis of RNAseq data", "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", "gatk4/createsomaticpanelofnormals": "Create a panel of normals constraining germline and artifactual sites for use with mutect2."}}, "target": "gatk4/createsomaticpanelofnormals", "target_idx": 4}
{"id": "noul_undeclared_process_file_inputs_20", "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_sentieon_rsempreparereference_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": {"openmsthirdparty/cometadapter": "Annotates MS/MS spectra using Comet.", "pairtools/restrict": "Assign restriction fragments to pairs", "sentieon/rsempreparereference": "Prepare a reference genome for RSEM", "sentieon/rsemcalculateexpression": "Calculate expression with RSEM", "tximeta/tximport": "Import transcript-level abundances and estimated counts for gene-level\nanalysis packages"}}, "target": "sentieon/rsempreparereference", "target_idx": 2}
{"id": "mod_vcf_impute_minimac4_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subworkflow to impute VCF files using MINIMAC4 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_minimac4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"aardvark_compare": null, "baysor_segfree": null, "bedtools_complement": null, "bcftools_annotate": null, "vcf_impute_minimac4": null}}, "target": "vcf_impute_minimac4", "target_idx": 4}
{"id": "resource_abritamr_run_3", "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_single": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "resource_bcftools_split_4", "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_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_bulk_multiqc_1_3", "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": "noul_modifying_channel_meta_inside_bash_script_block_15", "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_bbmap_bbduk_0", "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": {"clame": "binning of metagenomic sequences", "bbmap/bbduk": "Adapter and quality trimming of sequencing reads", "adapterremoval": "Trim sequencing adapters and collapse overlapping reads", "coptr/index": "Indexes a directory of fasta files for use with CoPTR", "chopper": "Filter and trim long read data."}}, "target": "bbmap/bbduk", "target_idx": 1}
{"id": "field_constraint_bam_0_4", "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": "qc_adapt_pacbio_hifi_0_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": "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_busco_plot_1", "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_high": null, "process_medium": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_chipseq_with_control_7_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": "Which columns should the samplesheet have for ChIP-seq with controls?", "criteria": {"sample,antibody,control": 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": "mod_shinyngs_validatefomcomponents_1", "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": {"geofetch": "geofetch is a command-line tool that downloads and organizes data and metadata from GEO and SRA", "rpbp_estimatemetagenebayesfactors": "Score how strongly each per-read-length metagene profile shows the\n3-nucleotide periodicity expected of active", "atlas_splitmerge": "split single end read groups by length and merge paired end reads", "shinyngs_validatefomcomponents": "validate consistency of feature and sample annotations with matrices and contrasts", "geoquery_getgeo": "Retrieves GEO data from the Gene Expression Omnibus (GEO)"}}, "target": "shinyngs_validatefomcomponents", "target_idx": 3}
{"id": "core_tool_bwa_mem_bare_2", "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": {"bwa_mem": null, "bowtie2": null, "star": null, "salmon": null, "minimap2": null}}, "target": "bwa_mem", "target_idx": 0}
{"id": "samplesheet_arch_vcf_annotation_pipeline_4_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": "What samplesheet columns are expected when inputs are: BGZF-compressed VCF files with companion Tabix index files?", "criteria": {"sample,bam,bai": null, "sample,bed": null, "sample,vcf,tbi": null, "sample,vcf": null}}, "target": "sample,vcf,tbi", "target_idx": 2}
{"id": "samplesheet_arch_ancient_dna_eager_7_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": "Which columns should the samplesheet have for grouped metagenomics?", "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": "subworkflow_pkg_fastq_align_dedup_bwameth_2", "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": {"Leave them out": null, "Use nf-core subworkflow fastq_align_dedup_bwameth": null, "Keep the modules in the main workflow": null, "Local subworkflow FASTQ_ALIGN_DEDUP_BWAMETH": null}}, "target": "Use nf-core subworkflow fastq_align_dedup_bwameth", "target_idx": 1}
{"id": "qc_adapt_qc_aggregate_2_12", "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_calder2_1", "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": {"kallistobustools_count": null, "agat_convertbed2gff": null, "calder2": null, "gemmi_cif2json": null, "agat_convertgff2bed": null}}, "target": "calder2", "target_idx": 2}
{"id": "qc_adapt_bulk_multiqc_1_8", "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_chipseq_with_control_6_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 are standard for ChIP-seq with IP and input control design input samplesheet?", "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_seqfu_stats_1", "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": {"rpbp_selectperiodicoffsets": "Pick the single best P-site offset for each read length from the\nper-(length, offset) Bayes factor table produ", "custom_collectstats": "Collects per-sample read-processing statistics (trimming, decontamination, alignment,\nfeature counting, and op", "seqfu_stats": "Statistics for FASTA or FASTQ files", "fcs_fcsadaptor": "Run NCBI's FCS adaptor on assembled genomes", "bcftools_stats": "Generates stats from VCF files"}}, "target": "seqfu_stats", "target_idx": 2}
{"id": "mod_refsolver_score_1", "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": {"bbmap_align": "Align short or PacBio reads to a reference genome using BBMap", "mmseqs_easysearch": "Searches for the sequences of a fasta file in a database using MMseqs2", "refsolver_score": "Score a query sequence dictionary against a reference using ref-solver", "bbmap_bbsplit": "Split sequencing reads by mapping them to multiple references simultaneously", "narfmap_align": "Performs fastq alignment to a reference using NARFMAP"}}, "target": "refsolver_score", "target_idx": 2}
{"id": "samplesheet_arch_bulk_rnaseq_pe_4_5", "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": "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": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 2}
{"id": "mod_plink_bcf_0", "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": {"find/concatenate": "A module for concatenation of gzipped or uncompressed files getting around UNIX terminal argument size", "plink/bcf": "Analyses binary variant call format (BCF) files using plink", "plink/exclude": "Exclude variant identifiers from plink bfiles", "atlasgeneannotationmanipulation/gtf2featureannotation": "Generate tables of feature metadata from GTF files", "plink/bmerge": "Merge a second PLINK binary fileset into the first and write a new combined PLINK binary fileset"}}, "target": "plink/bcf", "target_idx": 1}
{"id": "intent_debug_error_8", "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", "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": "debug_error", "target_idx": 2}
{"id": "pipe_all101_crisprseq_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for crispr analysis? Specific context: 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": {"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", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "lsmquant": "A pipeline for processing and analysis of light-sheet microscopy images. [3dunet, image-analysis, image-processing]", "hicar": "Pipeline for HiCAR data, a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chrom", "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", "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, ", "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": 1}
{"id": "qc_adapt_targeted_amplicon_0_1", "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": "samplesheet_arch_epigenomics_hic_5_5", "category": "samplesheet_schema", "state": {"assay": "Hi-C chromosome conformation capture mapping", "first_step": "FASTQC", "template": "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,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": "mod_pirate_0", "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": {"pirate": "Pangenome toolbox for bacterial genomes", "star/starsolo": "Create a counts matrix for single-cell data using STARSolo, handling cell barcodes and UMI information.", "samtools/fastq": "Converts a SAM/BAM/CRAM file to FASTQ", "agat/convertbed2gff": "Takes a bed12 file and converts to a GFF3 file", "agat/convertgff2bed": "Takes a GFF3 file and converts to a bed12 file"}}, "target": "pirate", "target_idx": 0}
{"id": "qc_adapt_qc_aggregate_0_0", "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_ngscheckmate_fastq_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 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": {"bcftools/csq": "bcftools Haplotype-aware consequence caller", "picard/splitsambynumberofreads": "Splits a SAM/BAM/CRAM file to multiple files. This tool splits the input query-grouped SAM/BAM/CRAM file into ", "ngscheckmate/fastq": "Determining whether sequencing data comes from the same individual by using SNP matching. This module generate", "ngscheckmate/patterngenerator": "Determining whether sequencing data comes from the same individual by using SNP matching. This module generate", "fastq_ngscheckmate": "Take a set of fastq files and run NGSCheckMate to determine whether samples match with each other, using a set"}}, "target": "ngscheckmate/fastq", "target_idx": 2}
{"id": "qc_adapt_bulk_multiqc_1_31", "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": "mod_bedgraph_bedclip_bedgraphtobigwig_0", "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": {"trgt/plot": null, "cnvkit/coverage": null, "bcftools/roh": null, "bedgraph_bedclip_bedgraphtobigwig": null, "bismark/coverage2cytosine": null}}, "target": "bedgraph_bedclip_bedgraphtobigwig", "target_idx": 3}
{"id": "schema_std_datasync_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/datasync. Description: nf-core/datasync is a system operation pipeline that provides several workflows for handling system operation / automation tasks.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/datasync.", "criteria": {"sample,run,group,short_reads_1,short_reads_2": null, "sample,input,output_path,checksum_md5,checksum_sha": null, "patient,vcf,tbi,dataset,tumour_sample": null, "fastq_1,fastq_2,group,replicate,md5_1": null}}, "target": "sample,input,output_path,checksum_md5,checksum_sha", "target_idx": 1}
{"id": "qc_adapt_bulk_multiqc_0_27", "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": "samplesheet_arch_pediatric_trio_somatic_2_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 should the input samplesheet have?", "criteria": {"family_id,sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": 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_wget_0", "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": {"aria2": "CLI Download utility", "wget": "The non-interactive network downloader", "blast/updateblastdb": "Downloads a BLAST database from NCBI", "samtools/dict": "Create a sequence dictionary file from a FASTA file", "hicexplorer/hicpca": "Computes PCA eigenvectors for a Hi-C matrix."}}, "target": "wget", "target_idx": 1}
{"id": "noul_named_output_channel_access_15", "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_artic_minion_1", "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_low": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "schema_std_ribomsqc_1_1", "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,group,path,ref,method": null, "id,raw_file": null, "fastq_1,fastq_2,group,replicate,control": null, "sample,fasta,protein,gbk,gff": null}}, "target": "id,raw_file", "target_idx": 1}
{"id": "mod_salmon_quant_0", "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": {"cooltools/insulation": "Calculate the diamond insulation scores and call insulating boundaries", "bowtie/build": "Create bowtie index for reference genome", "chromap/index": "Indexes a fasta reference genome ready for chromatin profiling.", "bcftools/index": "Index VCF tools", "salmon/quant": "gene/transcript quantification with Salmon"}}, "target": "salmon/quant", "target_idx": 4}
{"id": "samplesheet_arch_proteomics_dia_1_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": "Which columns should the 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": "schema_std_hadge_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/hadge", "description": "Comprehensive pipeline for donor demultiplexing in single cell", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/hadge?", "criteria": {"sample,bam,pbi,fail,repeat_id": null, "sample_id,idat_red,idat_green,group": null, "SAMPLE_ID,RCC_FILE,RCC_FILE_NAME,TIME,TREATMENT": null, "sample,bam,vcf,rna_matrix,hto_matrix": null}}, "target": "sample,bam,vcf,rna_matrix,hto_matrix", "target_idx": 3}
{"id": "pipe_all101_viralrecon_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for amplicon. 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", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples [amplicon, artic, assembly]", "kmermaid": " k-mer similarity analysis pipeline [k-mer, kmer, kmer-counting]", "stableexpression": "This pipeline is designed to identify the most stable genes in one or more expression datasets (RNA-seq / Microarray). T", "circdna": "Pipeline for the identification of extrachromosomal circular DNA (ecDNA) from Circle-seq, WGS, and ATAC-seq data that we", "magmap": "Best-practice analysis pipeline for mapping reads to a (large) collections of genomes", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 [16s, 18s, amplicon-sequencing]", "viralintegration": "Analysis pipeline for the identification of viral integration events in genomes using a chimeric read approach. [chimeri"}}, "target": "viralrecon", "target_idx": 1}
{"id": "samplesheet_arch_amplicon_16s_paired_0_5", "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 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_meryl_histogram_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": {"bcftools_sort": "Sorts VCF files", "meryl_histogram": "A genomic k-mer counter (and sequence utility) with nice features.", "bcftools_call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "fastk_merge": "A tool to merge FastK histograms", "ganon_classify": "Classify FASTQ files against ganon database"}}, "target": "meryl_histogram", "target_idx": 1}
{"id": "mod_seqkit_fx2tab_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert FASTA/Q to tabular format, and provide various information, like sequence length, GC content/GC skew. (tools: seqkit)?", "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", "proseg/proseg": "Proseg (probabilistic segmentation) is a cell segmentation method for in situ spatial transcriptomics.", "jellyfish/count": "Efficiently counts k-mers from DNA sequencing reads using a fast, memory-efficient, parallelized algorithm", "amrfinderplus/update": "Identify antimicrobial resistance in gene or protein sequences", "seqkit/fx2tab": "Convert FASTA/Q to tabular format, and provide various information, like sequence length, GC content/GC skew."}}, "target": "seqkit/fx2tab", "target_idx": 4}
{"id": "resource_admixture_5", "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": "pipe_all101_proteinfold_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for alphafold2. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"drugresponseeval": "Pipeline for testing drug response prediction models in a statistically and biologically sound way. [cell-lines, cross-v", "fetchngs": "Pipeline to fetch metadata and raw FastQ files from public databases [ddbj, download, ena]", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "hicar": "Pipeline for HiCAR data, a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chrom", "smrnaseq": "A small-RNA sequencing analysis pipeline [small-rna, smrna-seq]", "rnadnavar": "Pipeline for RNA and DNA integrated analysis for somatic mutation detection", "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", "stableexpression": "This pipeline is designed to identify the most stable genes in one or more expression datasets (RNA-seq / Microarray). T", "proteinfold": "Protein 3D structure prediction pipeline [alphafold2, colabfold, esmfold]"}}, "target": "proteinfold", "target_idx": 9}
{"id": "pipe_all101_demo_0", "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": {"molkart": null, "rnadnavar": null, "marsseq": null, "mnaseseq": null, "demo": null, "readsimulator": null, "funcscan": null, "airrflow": null}}, "target": "demo", "target_idx": 4}
{"id": "samplesheet_arch_bulk_small_rna_4_3", "category": "samplesheet_schema", "state": {"assay": "Small RNA / miRNA sequencing", "first_step": "FASTQC", "template": "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,vcf": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "samplesheet_arch_methylseq_bisulfite_2_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 should the input samplesheet have?", "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_bbmap_bbsplit_0", "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_medium": null, "process_single": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "intent_build_pipeline_2", "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", "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": "field_constraint_fastq_2_2_7", "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, "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": "schema_std_genomicrelatedness_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/genomicrelatedness. Description: Bioinformatics pipeline for estimating genetic relatedness from low-coverage whole-genome sequencing (sWGS) data.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/genomicrelatedness.", "criteria": {"sample,run,group,short_reads_1,short_reads_2": null, "patient,sample,fastq_1,fastq_2,bam": null, "sample,fastq_1,fastq_2,bam,cram": null, "sample,fastq_1,fastq_2,barcode_details": null}}, "target": "sample,fastq_1,fastq_2,bam,cram", "target_idx": 2}
{"id": "resource_adapterremoval_0", "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_medium": null, "process_low": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_singlecell_multiqc_1_35", "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_rapidnj_1", "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": {"hypo": "Assembly polisher using short (and long) reads", "svync": "A tool to standardize VCF files from structural variant callers", "epang_split": "splits an alignment into reference and query parts", "clipkit": "A multiple sequence alignment-trimming algorithm for accurate phylogenomic inference.", "rapidnj": "Produces a Newick format phylogeny from a multiple sequence alignment using a Neighbour-Joining algorithm. Cap"}}, "target": "rapidnj", "target_idx": 4}
{"id": "field_constraint_sample_1_7", "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_plotsr_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Plotsr generates high-quality visualisation of synteny and structural rearrangements between multiple genomes. (tools: plotsr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cellrangeratac/count": "Module to use Cell Ranger's ATAC pipelines analyze sequencing data produced from Chromium Single Cell ATAC.", "agat/spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "odgi/layout": "Establish 2D layouts of the graph using path-guided stochastic gradient descent. The graph must be sorted and ", "agat/spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "plotsr": "Plotsr generates high-quality visualisation of synteny and structural rearrangements between multiple genomes."}}, "target": "plotsr", "target_idx": 4}
{"id": "intent_debug_error_15", "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": "samplesheet_arch_scrna_multiome_2_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 should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,rna_fastq,atac_fastq": null, "sample,matrix": null, "sample,fastq_1,fastq_2,feature_type": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 3}
{"id": "resource_angsd_gl_3", "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_high": null, "process_long": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_faire_seq_chromatin_2_2", "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 input samplesheet have?", "criteria": {"sample,bam,bai": 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_agat_spaddintrons_1", "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_spkeeplongestisoform": "Filters GFF records to keep only the longest isoform per gene", "tbprofiler_profile": "A tool to detect resistance and lineages of M. tuberculosis genomes", "cellranger_multi": "Module to use Cell Ranger's pipelines to analyze sequencing data produced from various Chromium technologies, ", "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."}}, "target": "agat_spaddintrons", "target_idx": 4}
{"id": "samplesheet_arch_cancer_somatic_tn_2_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 should the input samplesheet have?", "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_riboseq_profiling_4_2", "category": "samplesheet_schema", "state": {"assay": "Ribosome profiling (Ribo-seq) footprint sequencing", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Single-end ribosome protected RNA fragments (RPFs) with strandedness?", "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": "mod_fgumi_extract_1", "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_zipperbams": "FGBIO tool to zip together an unmapped and mapped BAM to transfer metadata into the output BAM", "fastqscreen_fastqscreen": "Align reads to multiple reference genomes using fastq-screen", "fgbio_callduplexconsensusreads": "Uses FGBIO CallDuplexConsensusReads to call duplex consensus sequences from reads generated from the same doub", "gatk4_denoisereadcounts": "Denoises read counts to produce denoised copy ratios"}}, "target": "fgumi_extract", "target_idx": 0}
{"id": "pipe_all101_circdna_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: 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": {"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", "lsmquant": "A pipeline for processing and analysis of light-sheet microscopy images. [3dunet, image-analysis, image-processing]", "genomeassembler": "Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads [genome-assembly]", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "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]", "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]", "fastqrepair": "A pipeline that can be used to recover corrupted FASTQ.gz files, drop or fix uncompliant reads, remove unpaired reads, a"}}, "target": "circdna", "target_idx": 1}
{"id": "mod_repeatmodeler_builddatabase_1", "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": {"fastqe": null, "repeatmodeler_builddatabase": null, "agat_spextractsequences": null, "pbtk_bam2fastq": null, "alignoth": null}}, "target": "repeatmodeler_builddatabase", "target_idx": 1}
{"id": "samplesheet_arch_singlecell_parse_splitseq_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/scrnaseq --input samplesheet.csv (Assay: Parse Biosciences Split-seq combinatorial barcoding)", "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,fastq_2": null, "sample,subpool,fastq_1,fastq_2": null}}, "target": "sample,subpool,fastq_1,fastq_2", "target_idx": 3}
{"id": "schema_std_hadge_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/hadge", "description": "Comprehensive pipeline for donor demultiplexing in single cell", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/hadge?", "criteria": {"sample,fastq_1,fastq_2,fasta,run_accession": null, "sample_id,name,description,path,path_2": null, "sample,bam,vcf,rna_matrix,hto_matrix": null, "sample,condition,assay,peak_file,footprinting": null}}, "target": "sample,bam,vcf,rna_matrix,hto_matrix", "target_idx": 2}
{"id": "samplesheet_arch_singlecell_parse_splitseq_4_4", "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": "What samplesheet columns are expected when inputs are: Combinatorial split-pool barcoded FASTQs with subpool annotations?", "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": "mod_spades_1", "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": {"spades": "Assembles a small genome (bacterial, fungal, viral)", "ribotish_quality": "Quality control of riboseq bam data", "agat_convertspgff2tsv": "Converts a GFF/GTF file into a TSV file", "blobtk_plot": "Creates differing styles of blobplots depending on provided arguments.", "abyss_abysspe": "ABySS is a de novo sequence assembler intended for short paired-end reads and genomes of all sizes."}}, "target": "spades", "target_idx": 0}
{"id": "qc_adapt_targeted_amplicon_1_5", "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": "schema_std_hicar_1_0", "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,fastq_1,fastq_2,bam,bai": null, "id,fasta": null, "fastq_1,fastq_2,group,replicate,md5_1": null, "ID,Sample,Condition,ReplicateFileName,Fasta": null}}, "target": "fastq_1,fastq_2,group,replicate,md5_1", "target_idx": 2}
{"id": "samplesheet_arch_ont_direct_rna_se_5_4", "category": "samplesheet_schema", "state": {"assay": "Single-end Oxford Nanopore direct RNA", "first_step": "NANOPLOT"}, "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,fastq_1": null, "sample,fast5": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "qc_adapt_qc_aggregate_1_18", "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_ucsc_bigwigaverageoverbed_0", "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": {"ucsc/bigwigaverageoverbed": "compute average score of bigwig over bed file", "deeptools/plotpca": "Generates principal component analysis (PCA) plot using a compressed matrix generated by multibamsummary or mu", "deeptools/bigwigcompare": "Compare two bigWig files based on the number of mapped reads", "qualimap/bamqccram": "Evaluate alignment data", "cnvkit/call": "Given segmented log2 ratio estimates (.cns), derive each segment’s absolute integer copy number"}}, "target": "ucsc/bigwigaverageoverbed", "target_idx": 0}
{"id": "resource_amps_2", "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_low": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "core_tool_deepvariant_bare_2", "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": {"clair3": null, "varscan2": null, "freebayes": null, "gatk_haplotypecaller": null, "deepvariant": null}}, "target": "deepvariant", "target_idx": 4}
{"id": "field_constraint_strandedness_1_2", "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": "resource_blast_makeblastdb_2", "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_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_star_starsolo_0", "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": {"ampcombi2/complete": "A submodule that merges all output summary tables from ampcombi/parsetables in one summary file.", "varlociraptor/callvariants": "Call variants for a given scenario specified with the varlociraptor calling grammar, preprocessed by varlocira", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files.", "star/starsolo": "Create a counts matrix for single-cell data using STARSolo, handling cell barcodes and UMI information.", "svtools/vcftobedpe": "Convert a VCF file to a BEDPE file."}}, "target": "star/starsolo", "target_idx": 3}