{"id": "schema_std_bacass_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/bacass", "description": "Simple bacterial assembly and annotation pipeline", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/bacass?", "criteria": {"sample,fastq_1,fastq_2,bam,seq_type": null, "sample,seed": null, "ID,R1,R2,LongFastQ,Fast5": null, "sample,condition,assay,peak_file,footprinting": null}}, "target": "ID,R1,R2,LongFastQ,Fast5", "target_idx": 2}
{"id": "core_tool_mutect2_bare_2", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Somatic short variant detection (SNVs and small indels) comparing matched tumor and normal sequencing data with Bayesian somatic likelihood filtering.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"vardict": null, "somaticsniper": null, "varscan2": null, "strelka2": null, "mutect2": null}}, "target": "mutect2", "target_idx": 4}
{"id": "mod_custom_addmostseverepli_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Annotate a VEP annotated VCF with the most severe pLi field (tools: custom)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ganon_table": "Generate a multi-sample report file from the output of ganon report runs", "deepvariant_rundeepvariant": "DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generat", "custom_addmostseverepli": "Annotate a VEP annotated VCF with the most severe pLi field", "atlasgeneannotationmanipulation_gtf2featureannotation": "Generate tables of feature metadata from GTF files", "agat_spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas"}}, "target": "custom_addmostseverepli", "target_idx": 2}
{"id": "mod_limma_differential_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: runs a differential expression analysis with Limma (tools: limma)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"yara_index": "Builds a YARA index for a reference genome", "shinyngs_app": "build and deploy Shiny apps for interactively mining differential abundance data", "xeniumranger_relabel": "The xeniumranger relabel module allows you to change the gene labels applied to decoded transcripts.", "deseq2_differential": "runs a differential expression analysis with DESeq2", "limma_differential": "runs a differential expression analysis with Limma"}}, "target": "limma_differential", "target_idx": 4}
{"id": "mod_seqsero2_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Salmonella serotype prediction from reads and assemblies (tools: seqsero2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"entrezdirect_xtract": "Queries an NCBI database using an UID", "agrvate": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants", "ltrharvest": "Predicts LTR retrotransposons using the parallel version of GenomeTools gt-ltrharvest\nutility included in the ", "amrfinderplus_update": "Identify antimicrobial resistance in gene or protein sequences", "seqsero2": "Salmonella serotype prediction from reads and assemblies"}}, "target": "seqsero2", "target_idx": 4}
{"id": "qc_adapt_bulk_multiqc_0_28", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For High-throughput bulk WGS multi-sample run, what is the recommended QC default for MultiQC?", "criteria": {"Swap for NanoPlot": null, "Drop MultiQC": null, "Keep MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "resource_bismark_summary_0", "category": "resource_profiling", "state": {"process": "BISMARK_SUMMARY", "tool": "bismark/summary", "description": "Uses Bismark report files of several samples in a run folder to generate a graphical summary HTML report."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_SUMMARY (Uses Bismark report files of several samples in a run folder to generate a graph) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_ont_metagenome_single_5_2", "category": "samplesheet_schema", "state": {"assay": "Long-read Oxford Nanopore environmental metagenomic sequencing", "first_step": "NANOPLOT", "inputs": "High molecular weight environmental metagenomic long reads per sampling site", "pipeline": "nf-core/mag"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/mag, determine the input samplesheet column structure for: Long-read Oxford Nanopore environmental metagenomic sequencing.", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,group": null, "sample,bam": null}}, "target": "sample,fastq_1,group", "target_idx": 2}
{"id": "samplesheet_arch_epigenomics_hic_0_2", "category": "samplesheet_schema", "state": {"assay": "Hi-C chromosome conformation capture mapping", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Hi-C chromosome conformation capture mapping?", "criteria": {"sample,bed": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "qc_adapt_bulk_multiqc_2_10", "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": "intent_debug_error_9", "category": "intent_routing", "state": "Classify this user request: \"ERROR ~ Error executing process > 'SAMTOOLS_SORT' (command not found, exit status 127)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": null, "debug_error": null, "ask_question": null, "build_pipeline": null}}, "target": "debug_error", "target_idx": 1}
{"id": "mod_savana_classify_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Classify structural variants using SAVANA (tools: savana)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"traitar/run": "Traitar3 - predict microbial phenotypes from genomic sequences using protein families", "savana/classify": "Classify structural variants using SAVANA", "conifer": "Calculate confidence scores from Kraken2 output", "hamronization/rgi": "Tool to convert and summarize RGI outputs using the hAMRonization specification.", "centrifuge/centrifuge": "Classifies metagenomic sequence data"}}, "target": "savana/classify", "target_idx": 1}
{"id": "field_constraint_bai_0_8", "category": "samplesheet_schema", "state": {"field_name": "bai", "datatype": "companion_index", "description": "Companion BAM index file"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'bai'?", "criteria": {"type: boolean": null, "pattern: ^\\S+\\.crai$": null, "pattern: ^\\S+\\.tbi$": null, "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 3}
{"id": "mod_jupyternotebook_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Render jupyter (or jupytext) notebooks to HTML reports. Supports parametrization\nthrough papermill. (tools: jupytext)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"scramble_clusteridentifier": "The cluster_identifier tool of Scramble identifies soft clipped clusters", "quarto_prerender": "Pre-render a Quarto document to markdown, including parametrization", "jupyternotebook": "Render jupyter (or jupytext) notebooks to HTML reports. Supports parametrization\nthrough papermill.", "paragraph_vcf2paragraph": "Convert a VCF file to a JSON graph", "rmarkdownnotebook": "Render an rmarkdown notebook. Supports parametrization."}}, "target": "jupyternotebook", "target_idx": 2}
{"id": "mod_seqkit_tab2fx_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert tabular format (first two/three columns) to FASTA/Q format. (tools: seqkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqkit/tab2fx": "Convert tabular format (first two/three columns) to FASTA/Q format.", "abritamr/run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes", "vclust/align": "The align command performs pairwise sequence alignments of viral genomes and provides similarity measures like", "nacho/qc": "NACHO (NAnostring quality Control dasHbOard) is developed for NanoString nCounter data.\nNanoString nCounter da", "agat/spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file."}}, "target": "seqkit/tab2fx", "target_idx": 0}
{"id": "noul_channel_factory_inside_process_body_0", "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": "noul_executor_support_15", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Nextflow supports executing tasks across Slurm, AWS Batch, Google Cloud Batch, and Kubernetes through the `executor` directive.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_stainwarpy_register_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Register H&E stained and Multiplexed tissue images using feature-based image registration (tools: stainwarpy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"stainwarpy/transformsegmask": null, "gatk4/variantstotable": null, "stainwarpy/extractchannel": null, "gatk4/genotypegvcfs": null, "stainwarpy/register": null}}, "target": "stainwarpy/register", "target_idx": 4}
{"id": "mod_umicollapse_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Deduplicate reads based on the mapping co-ordinate and the UMI attached to the read. (tools: umicollapse)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pairtools/dedup": "Find and remove PCR/optical duplicates", "gtdbtk/gtdbtoncbimajorityvote": "Converts the output classifications of GTDB-TK from GTDB taxonomy to NCBI taxonomy", "amulety/antiberta2": "A module to create antiberta2 embeddings of antibody (BCR) amino acid sequences using amulety.", "umicollapse": "Deduplicate reads based on the mapping co-ordinate and the UMI attached to the read.", "bam_dedup_umi": "BAM deduplication with UMI processing for both genome and transcriptome alignments"}}, "target": "umicollapse", "target_idx": 3}
{"id": "pipe_all101_references_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for genome analysis? Specific context: nf-core/references is a bioinformatics pipeline that build references, for multiple use cases. Topics: genome, references, reproducibility. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples [amplicon, artic, assembly]", "pixelator": "Pipeline to generate Proximity Network Assay data with Pixelator (Pixelgen Technologies AB) [molecular-pixelation, pixel", "variantprioritization": "Bioinformatics analysis pipeline for the functional annotation and translation of somatic SNVs/InDels and copy number ab", "denovotranscript": "A pipeline for de novo transcriptome assembly of paired-end short reads from bulk RNA-seq [denovo-assembly, rna-seq, tra", "references": "nf-core/references is a bioinformatics pipeline that build references, for multiple use cases [genome, references, repro", "stableexpression": "This pipeline is designed to identify the most stable genes in one or more expression datasets (RNA-seq / Microarray). T", "hgtseq": "A pipeline to investigate horizontal gene transfer from NGS data [bwa-mem, bwa-mem2, fastqc]", "phyloplace": "nf-core/phyloplace is a bioinformatics best-practice analysis pipeline that performs phylogenetic placement with EPA-NG.", "nascent": "Nascent Transcription Processing Pipeline [gro-seq, nascent, pro-seq]", "clipseq": "CLIP sequencing analysis pipeline for QC, pre-mapping, genome mapping, UMI deduplication, and multiple peak-calling opti"}}, "target": "references", "target_idx": 4}
{"id": "samplesheet_arch_methylseq_bisulfite_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/methylseq) for Whole-Genome Bisulfite Sequencing (WGBS / EM-seq). Input files: Bisulfite-converted or enzymatic methyl-converted paired-end FASTQs.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Whole-Genome Bisulfite Sequencing (WGBS / EM-seq)?", "criteria": {"sample,vcf": null, "sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "qc_adapt_pacbio_hifi_2_44", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "resource_bedtools_complement_5", "category": "resource_profiling", "state": {"process": "BEDTOOLS_COMPLEMENT", "tool": "bedtools/complement", "description": "Returns all intervals in a genome that are not covered by at least one interval in the input BED/GFF/VCF file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_COMPLEMENT (Returns all intervals in a genome that are not covered by at least one interval ) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_kmcp_merge_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge search results from multiple databases. (tools: kmcp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"saltshaker_classify": "mtDNA deletion and duplication classification downstream of mitosalt", "argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD).", "deeptools_computematrix": "calculates scores per genome regions for other deeptools plotting utilities", "bracken_combinebrackenoutputs": "Combine output of metagenomic samples analyzed by bracken.", "kmcp_merge": "Merge search results from multiple databases."}}, "target": "kmcp_merge", "target_idx": 4}
{"id": "samplesheet_arch_dual_rnaseq_host_pathogen_3_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/dualrnaseq) for Dual RNA-seq simultaneous host and pathogen transcriptomics. Input files: Paired-end FASTQs from infected tissue undergoing dual mapping to human and pathogen.", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Dual RNA-seq simultaneous host and pathogen transcriptomics with entry step FASTQC.", "criteria": {"sample,host_fasta": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,host,pathogen": null}}, "target": "sample,fastq_1,fastq_2,host,pathogen", "target_idx": 3}
{"id": "samplesheet_arch_pediatric_trio_somatic_0_4", "category": "samplesheet_schema", "state": {"technology": "Clinical Genetics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end FASTQs tracking patient, sample, tissue status (normal/tumor), and maternal/paternal lineage"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Pediatric cancer trio (Child Proband tumor, Proband germline, Parents)?", "criteria": {"family_id,sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "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": "resource_busco_generateplot_0", "category": "resource_profiling", "state": {"process": "BUSCO_GENERATEPLOT", "tool": "busco/generateplot", "description": "BUSCO plot generation tool"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BUSCO_GENERATEPLOT (BUSCO plot generation tool) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "noul_multiple_script_sections_invalid_15", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"A process definition in Nextflow can declare multiple `script:` sections within the same process block.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "qc_adapt_pacbio_hifi_0_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": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "resource_angsd_dosaf_2", "category": "resource_profiling", "state": {"process": "ANGSD_DOSAF", "tool": "angsd/dosaf", "description": "Estimate site allele frequencies from BAM files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANGSD_DOSAF (Estimate site allele frequencies from BAM files.) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_repeatmasker_rmouttogff3_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A utility script to assist to convert old RepeatMasker *.out files to version 3 gff files. (tools: repeatmasker)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biobambam/bamsormadup": "Parallel sorting and duplicate marking", "bedtools/sort": "Sorts a feature file by chromosome and other criteria.", "repeatmasker/rmouttogff3": "A utility script to assist to convert old RepeatMasker *.out files to version 3 gff files.", "pbtk/pbindex": "Minimalistic tool which creates an index file that enables random access into PacBio BAM files", "molkartgarage/clahe": "Contrast-limited adjusted histogram equalization (CLAHE) on single-channel tif images."}}, "target": "repeatmasker/rmouttogff3", "target_idx": 2}
{"id": "resource_blast_blastp_1", "category": "resource_profiling", "state": {"process": "BLAST_BLASTP", "tool": "blast/blastp", "description": "BLASTP (Basic Local Alignment Search Tool- Protein) compares an amino acid (protein) query sequence against a protein database"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLAST_BLASTP (BLASTP (Basic Local Alignment Search Tool- Protein) compares an amino acid (prot) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_cancer_tumor_only_4_4", "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": "What samplesheet columns are expected when inputs are: Paired-end FASTQ reads from tumor biopsy without matched normal?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_vsearch_fastqfilter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs quality filtering and / or conversion of a FASTQ file to FASTA format. (tools: vsearch)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vsearch_fastqfilter": "Performs quality filtering and / or conversion of a FASTQ file to FASTA format.", "vsearch_dereplicate": "Merge strictly identical sequences contained in filename. Identical sequences are defined as having the same l", "vsearch_cluster": "Cluster sequences using a single-pass, greedy centroid-based clustering algorithm.", "sylphtax_merge": "Merge multiple taxonomic profiles from sylphtaxt/taxprof into a tsv table", "optitype": "Perform HLA-I typing of sequencing data"}}, "target": "vsearch_fastqfilter", "target_idx": 0}
{"id": "samplesheet_arch_ancient_dna_eager_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/eager --input samplesheet.csv (Assay: Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment)", "question": {"type": "choice", "instructions": "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,fastq_1,fastq_2": null, "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 1}
{"id": "samplesheet_arch_methylseq_bisulfite_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/methylseq --input samplesheet.csv (Assay: Whole-Genome Bisulfite Sequencing (WGBS / EM-seq))", "question": {"type": "choice", "instructions": "Which columns are standard for Whole-Genome Bisulfite Sequencing (WGBS / EM-seq) input samplesheet?", "criteria": {"sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,cpg,methylation": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "resource_bedtools_merge_1", "category": "resource_profiling", "state": {"process": "BEDTOOLS_MERGE", "tool": "bedtools/merge", "description": "combines overlapping or “book-ended” features in an interval file into a single feature which spans all of the combined features."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_MERGE (combines overlapping or “book-ended” features in an interval file into a single ) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_saltshaker_classify_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: mtDNA deletion and duplication classification downstream of mitosalt (tools: saltshaker)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"saltshaker_plot": "mtDNA deletion and duplication plotting downstream of mitosalt", "saltshaker_classify": "mtDNA deletion and duplication classification downstream of mitosalt", "gatk4_haplotypecaller": "Call germline SNPs and indels via local re-assembly of haplotypes", "glimpse2_chunk": "Defines chunks where to run imputation", "haplogrep3_classify": "classification into haplogroups"}}, "target": "saltshaker_classify", "target_idx": 1}
{"id": "pipe_all101_funcscan_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: (Meta-)genome screening for functional and natural product gene sequences. Topics: amp, amr, antibiotic-resistance, antimicrobial-peptides, antimicrobial-resistance-genes, arg. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"longraredisease": null, "hlatyping": null, "hgtseq": null, "smrnaseq": null, "scrnaseq": null, "phyloplace": null, "funcscan": null, "readsimulator": null, "differentialabundance": null, "proteinfamilies": null}}, "target": "funcscan", "target_idx": 6}
{"id": "samplesheet_arch_spatial_visium_4_0", "category": "samplesheet_schema", "state": {"assay": "10x Visium spatial transcriptomics with histology image", "first_step": "FASTQC", "inputs": "Spatial cDNA FASTQs paired with high-resolution brightfield tissue image and slide coordinates", "pipeline": "nf-core/spatialaxe"}, "question": {"type": "choice", "instructions": "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,fastq_1,image": 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_pbjasmine_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Identify specific base modifications in PacBio HiFi reads by analyzing polymerase kinetic signatures (tools: pbjasmine)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"finaletoolkit/wps": "Calculate the windowed protection score (WPS; Snyder et al., 2016)\nfrom a BAM file and a list of transcription", "gatk4/createsequencedictionary": "Creates a sequence dictionary for a reference sequence", "pbjasmine": "Identify specific base modifications in PacBio HiFi reads by analyzing polymerase kinetic signatures", "agat/spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "agat/spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas"}}, "target": "pbjasmine", "target_idx": 2}
{"id": "samplesheet_arch_mira_influenza_sc2_3_5", "category": "samplesheet_schema", "state": "nextflow run custom/mira-nf --input samplesheet.csv (Assay: Custom MIRA-NF Influenza / SC2 pipeline)", "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,bam": null, "sample,fastq_1": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "pipe_all101_pangenome_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Renders a collection of sequences into a pangenome graph. https://doi.org/10.1093/bioinformatics/btae609.. Topics: pangenome. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"pangenome": null, "createtaxdb": null, "scnanoseq": null, "drugresponseeval": null, "differentialabundance": null, "proteogenomicsdb": null, "lsmquant": null, "methylong": null, "phaseimpute": null, "mnaseseq": null}}, "target": "pangenome", "target_idx": 0}
{"id": "mod_antismash_antismash_0", "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": {"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", "samtools/flagstat": "Counts the number of alignments in a BAM/CRAM/SAM file for each FLAG type", "autocycler/compress": "Package candidate assemblies for clustering by Autocycler.", "deepbgc/pipeline": "DeepBGC detects BGCs in bacterial and fungal genomes using deep learning."}}, "target": "antismash/antismash", "target_idx": 0}
{"id": "mod_paragraph_vcf2paragraph_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert a VCF file to a JSON graph (tools: paragraph)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"trgt_genotype": "Tandem repeat genotyping from PacBio HiFi data", "dssp_mkdssp": "Calculates secondary structure assignments from PDB files using mkdssp (DSSP).\nDSSP is a standard tool for ass", "paragraph_vcf2paragraph": "Convert a VCF file to a JSON graph", "aardvark_compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "annotsv_annotsv": "Annotation and Ranking of Structural Variation"}}, "target": "paragraph_vcf2paragraph", "target_idx": 2}
{"id": "qc_adapt_pe_illumina_fastqc_2_16", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Standard Paired-end Illumina RNA-seq (short_reads_150bp).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_gatk4_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: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqkit/replace": "Use seqkit to find/replace strings within sequences and sequence headers", "picard/addorreplacereadgroups": "Assigns all the reads in a file to a single new read-group", "purecn/coverage": "Calculate intervals coverage for each sample. N.B. the tool can not handle staging files with symlinks, stageI", "gatk4/addorreplacereadgroups": "Assigns all the reads in a file to a single new read-group", "angsd/soapsnpcalibration": "Generate ANGSD SOAPsnp genotype likelihood calibration files (counts/quality matrices) from BAM alignments."}}, "target": "gatk4/addorreplacereadgroups", "target_idx": 3}
{"id": "samplesheet_arch_cageseq_transcription_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/cageseq", "assay_type": "CAGE-seq 5-prime capped transcript end sequencing", "data_format": "Single-end capped 5-prime cDNA tags for transcription start site (TSS) mapping"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for CAGE-seq 5-prime capped transcript end sequencing with entry step FASTQC.", "criteria": {"sample,vcf": null, "sample,fastq_1": null, "sample,tss_bed": null, "sample,bam": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "subworkflow_pkg_vcf_phase_shapeit5_2", "category": "subworkflow_packaging", "state": {"subworkflow": "VCF_PHASE_SHAPEIT5", "modules": ["glimpse2/chunk", "shapeit5/phasecommon", "shapeit5/ligate", "bcftools/index"], "description": "Subworkflow to phase a reference panel VCF file using SHAPEIT5."}, "question": {"type": "choice", "instructions": "How should VCF_PHASE_SHAPEIT5 (glimpse2/chunk, shapeit5/phasecommon, shapeit5/ligate, bcftools/index) be structured in DSL2?", "criteria": {"Local subworkflow VCF_PHASE_SHAPEIT5": null, "Leave them out": null, "Use nf-core subworkflow vcf_phase_shapeit5": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow vcf_phase_shapeit5", "target_idx": 2}
{"id": "samplesheet_arch_cancer_somatic_bam_2_4", "category": "samplesheet_schema", "state": {"assay": "Somatic tumor-normal calling from pre-aligned BAM files", "first_step": "MUTECT2", "inputs": "Coordinate-sorted BAMs with index for tumor and normal samples", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,vcf": null, "patient,sample,status,bam,bai": null, "sample,bam,bai": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 1}
{"id": "samplesheet_arch_taxprofiler_shotgun_3_0", "category": "samplesheet_schema", "state": {"assay": "Multi-taxonomic profiling of complex metagenomic shotgun reads", "first_step": "FASTQC"}, "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,kraken_db": null, "sample,run_accession,instrument_platform,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 1}
{"id": "subworkflow_pkg_bam_tumor_only_somatic_variant_calling_gatk_3", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_TUMOR_ONLY_SOMATIC_VARIANT_CALLING_GATK", "modules": ["gatk4/mutect2", "gatk4/getpileupsummaries", "gatk4/calculatecontamination", "gatk4/filtermutectcalls"], "description": "Perform variant calling on a single tumor sample using mutect2 tumor only mode."}, "question": {"type": "choice", "instructions": "How should BAM_TUMOR_ONLY_SOMATIC_VARIANT_CALLING_GATK (gatk4/mutect2, gatk4/getpileupsummaries, gatk4/calculatecontamination, gatk4/filtermutectcalls) be structured in DSL2?", "criteria": {"Use nf-core subworkflow bam_tumor_only_somatic_variant_calling_gatk": null, "Local subworkflow BAM_TUMOR_ONLY_SOMATIC_VARIANT_CALLING_GATK": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Use nf-core subworkflow bam_tumor_only_somatic_variant_calling_gatk", "target_idx": 0}
{"id": "subworkflow_pkg_fastq_align_dedup_bismark_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_DEDUP_BISMARK", "modules": ["bismark/align", "samtools/sort", "samtools/index", "bismark/deduplicate", "bismark/methylationextractor", "bismark/coverage2cytosine", "bismark/report", "bismark/summary"], "description": "Align BS-Seq reads to a reference genome using bismark, deduplicate and sort"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_DEDUP_BISMARK (bismark/align, samtools/sort, samtools/index, bismark/deduplicate, bismark/methylationextractor, bismark/coverage2cytosine, bismark/report, bismark/summary) be structured in DSL2?", "criteria": {"Local subworkflow FASTQ_ALIGN_DEDUP_BISMARK": null, "Use nf-core subworkflow fastq_align_dedup_bismark": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Use nf-core subworkflow fastq_align_dedup_bismark", "target_idx": 1}
{"id": "mod_splitubam_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: split one ubam into multiple, per line, fast (tools: splitubam)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rpbp_selectperiodicoffsets": "Pick the single best P-site offset for each read length from the\nper-(length, offset) Bayes factor table produ", "autocycler_cluster": "Cluster replicons in compressed assemblies with Autocycler.", "autocycler_subsample": "Downsample long-read sequencing data to the requested coverage using Autocycler.", "splitubam": "split one ubam into multiple, per line, fast", "sentieon_tnhaplotyper2": "Tnhaplotyper2 performs somatic variant calling on the tumor-normal matched pairs."}}, "target": "splitubam", "target_idx": 3}
{"id": "qc_adapt_illumina_novaseq_2_41", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_myloasm_1", "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": {"abyss_abysspe": "ABySS is a de novo sequence assembler intended for short paired-end reads and genomes of all sizes.", "survivor_bedpetovcf": "Converts a bedpe file to a VCF file (beta version)", "abacas": "Contiguate draft genome assembly", "myloasm": "Myloasm is a de novo metagenome assembler for long-read sequencing data.\nIt takes sequencing reads and outputs", "fastq_find_mirna_mirdeep2": "This subworkflow identifies miRNAs from FASTQ files using miRDeep2. The workflow converts FASTQ to FASTA, proc"}}, "target": "myloasm", "target_idx": 3}
{"id": "mod_ribocode_ribocode_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Call ORFs with RiboCode from Ribo-Seq data (tools: ribocode)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ribocode_ribocode": "Call ORFs with RiboCode from Ribo-Seq data", "ribocode_gtfupdate": "Update GTF annotation file for RiboCode compatibility", "ska_distance": "Calculate pairwise distances and basic clustering from SKA sketches", "ismapper": "Identify insertion sites positions in bacterial genomes", "custom_orfcollapse": "Collapse small ORFs that share an amino-acid sequence cluster into a single\ncatalogue entry. Pair with `custom"}}, "target": "ribocode_ribocode", "target_idx": 0}
{"id": "samplesheet_arch_methylseq_bisulfite_2_4", "category": "samplesheet_schema", "state": {"assay": "Whole-Genome Bisulfite Sequencing (WGBS / EM-seq)", "first_step": "FASTQC", "inputs": "Bisulfite-converted or enzymatic methyl-converted paired-end FASTQs", "pipeline": "nf-core/methylseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,cpg,methylation": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "samplesheet_arch_metatranscriptome_denovo_2_4", "category": "samplesheet_schema", "state": {"assay": "Environmental community metatranscriptomics de novo assembly", "first_step": "FASTQC", "inputs": "Paired-end total RNA reads from complex microbial communities with ribosomal RNA filtering", "pipeline": "nf-core/metatdenovo"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,rrna_fasta": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,environment": null}}, "target": "sample,fastq_1,fastq_2,environment", "target_idx": 3}
{"id": "noul_deprecated_dsl1_set_keyword_14", "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_fastq_2_0_3", "category": "samplesheet_schema", "state": {"field_name": "fastq_2", "datatype": "conditional_file_pattern", "description": "Path to read 2 FASTQ file for paired-end sequencing"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'fastq_2'?", "criteria": {"type: required string": null, "pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null, "enum: [0, 1]": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 2}
{"id": "samplesheet_arch_ancient_dna_eager_7_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/eager --input samplesheet.csv (Assay: Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for grouped metagenomics?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null, "sample,library_id,fastq_1,fastq_2": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 2}
{"id": "subworkflow_pkg_bam_taps_conversion_2", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_TAPS_CONVERSION", "modules": ["rastair/mbias", "rastair/call", "rastair/methylkit", "rastair/mbiasparser"], "description": "Uses rastair to assess C->T conversion as a readout for methylation in a genome-wide basis"}, "question": {"type": "choice", "instructions": "How should BAM_TAPS_CONVERSION (rastair/mbias, rastair/call, rastair/methylkit, rastair/mbiasparser) be structured in DSL2?", "criteria": {"Use nf-core subworkflow bam_taps_conversion": null, "Keep the modules in the main workflow": null, "Local subworkflow BAM_TAPS_CONVERSION": null, "Leave them out": null}}, "target": "Use nf-core subworkflow bam_taps_conversion", "target_idx": 0}
{"id": "qc_adapt_bulk_multiqc_2_1", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Keep MultiQC": null, "Keep FastQC": null, "Swap for NanoPlot": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "mod_sawfish_jointcall_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Joint calling of structural variants from multiple samples using Sawfish (tools: sawfish)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"epic2/epic2": "Domain calling of broad enriched genomic regions of ChIP-seq, Cut&Run or Cut&Tag", "sniffles": "structural-variant calling with sniffles", "sawfish/discover": "SV candidate discovery from PacBio HiFi data", "sawfish/jointcall": "Joint calling of structural variants from multiple samples using Sawfish", "bam_stringtie_merge": "Assemble transcripts from sorted BAM alignments using StringTie, then merge per-sample transcript GTFs into a "}}, "target": "sawfish/jointcall", "target_idx": 3}
{"id": "noul_subworkflow_structural_blocks_12", "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_bcftools_pluginsplit_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Split VCF by sample, creating single- or multi-sample VCFs. (tools: pluginsplit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/determinegermlinecontigploidy": "Determines the baseline contig ploidy for germline samples given counts data", "bamtools/split": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "sylph/query": "Sylph query command for querying genome databases against reads/metagenomes", "bcftools/split": "Split a vcf file into files per chromosome", "bcftools/pluginsplit": "Split VCF by sample, creating single- or multi-sample VCFs."}}, "target": "bcftools/pluginsplit", "target_idx": 4}
{"id": "mod_biscuit_qc_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform basic quality control on a BAM file generated with Biscuit (tools: biscuit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biscuit_mergecg": "Merges methylation information for opposite-strand C's in a CpG context", "biscuit_bsconv": "Summarize and/or filter reads based on bisulfite conversion rate", "find_unpigz": "A module for decompressing a large number of gzipped files, getting around the UNIX terminal argument limit", "rtgtools_format": "Converts the contents of sequence data files (FASTA/FASTQ/SAM/BAM) into the RTG Sequence Data File (SDF) forma", "biscuit_qc": "Perform basic quality control on a BAM file generated with Biscuit"}}, "target": "biscuit_qc", "target_idx": 4}
{"id": "mod_icountmini_sigxls_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Runs iCount sigxls on a BED file of crosslinks (tools: icount)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"macsyfinder_download": "Download MacSyFinder models using msf_data", "peka": "Runs PEKA CLIP peak k-mer analysis", "icountmini_sigxls": "Runs iCount sigxls on a BED file of crosslinks", "plink2_vcf": "Import variant genetic data using plink2", "clippy": "Runs the Clippy CLIP peak caller"}}, "target": "icountmini_sigxls", "target_idx": 2}
{"id": "schema_std_datasync_2_0", "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,fastq_1,fastq_2,genome": null, "sample,short_reads_fastq_1,short_reads_fastq_2,long_reads_fastq_1": null, "sample,input,output_path,checksum_md5,checksum_sha": null, "gene_name,alignment,tree,suite,tool": null}}, "target": "sample,input,output_path,checksum_md5,checksum_sha", "target_idx": 2}
{"id": "resource_bedtools_nuc_4", "category": "resource_profiling", "state": {"process": "BEDTOOLS_NUC", "tool": "bedtools/nuc", "description": "Profiles the nucleotide content of intervals in a fasta file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_NUC (Profiles the nucleotide content of intervals in a fasta file.) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "field_constraint_bai_0_13", "category": "samplesheet_schema", "state": {"field_name": "bai", "datatype": "companion_index", "description": "Companion BAM index file"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'bai'?", "criteria": {"pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "type: boolean": null, "pattern: ^\\S+\\.crai$": null, "pattern: ^\\S+\\.tbi$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 0}
{"id": "samplesheet_arch_pediatric_trio_somatic_2_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Pediatric cancer trio (Child Proband tumor, Proband germline, Parents). Input files: Paired-end FASTQs tracking patient, sample, tissue status (normal/tumor), and maternal/paternal lineage.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,bam,bai": null, "family_id,sample,fastq_1,fastq_2": null, "family_id,patient,sample,status,sex,fastq_1,fastq_2": null}}, "target": "family_id,patient,sample,status,sex,fastq_1,fastq_2", "target_idx": 3}
{"id": "samplesheet_arch_cancer_tumor_only_0_0", "category": "samplesheet_schema", "state": {"assay": "Tumor-only somatic variant calling without matched normal", "first_step": "FASTQC", "inputs": "Paired-end FASTQ reads from tumor biopsy without matched normal", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Tumor-only somatic variant calling without matched normal?", "criteria": {"sample,fastq_1": 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": "resource_bandage_image_3", "category": "resource_profiling", "state": {"process": "BANDAGE_IMAGE", "tool": "bandage/image", "description": "Render an assembly graph in GFA 1.0 format to PNG and SVG image formats"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BANDAGE_IMAGE (Render an assembly graph in GFA 1.0 format to PNG and SVG image formats) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_busco_phylogenomics_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Construct species phylogenies using BUSCO proteins (tools: busco)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"busco_phylogenomics": "Construct species phylogenies using BUSCO proteins", "fgbio_fastqtobam": "Using the fgbio tools, converts FASTQ files sequenced into unaligned BAM or CRAM files possibly moving the UMI", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "alignoth": "Creating alignment plots from bam files", "multiqcsav": "Aggregate results from bioinformatics analyses across many samples into a single report, with support for mult"}}, "target": "busco_phylogenomics", "target_idx": 0}
{"id": "qc_adapt_bulk_multiqc_0_25", "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": "mod_custom_sratoolsncbisettings_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Test for the presence of suitable NCBI settings or create them on the fly. (tools: sratools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"entrezdirect_esummary": "Queries an NCBI database using Unique Identifier(s)", "fcs_fcsadaptor": "Run NCBI's FCS adaptor on assembled genomes", "crabz_compress": "Compress files with crabz", "gget_gget": "gget is a free, open-source command-line tool and Python package that enables efficient querying of genomic da", "custom_sratoolsncbisettings": "Test for the presence of suitable NCBI settings or create them on the fly."}}, "target": "custom_sratoolsncbisettings", "target_idx": 4}
{"id": "noul_workflow_completion_lifecycle_hook_1", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `workflow.onComplete { }` handler executes after all pipeline processes finish.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "field_constraint_bam_0_10", "category": "samplesheet_schema", "state": {"field_name": "bam", "datatype": "file_pattern", "description": "Path to aligned binary sequence alignment (BAM) file"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'bam'?", "criteria": {"pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null, "format: uri": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 1}
{"id": "mod_wgsim_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: simulating sequence reads from a reference genome (tools: wgsim)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amrfinderplus_update": "Identify antimicrobial resistance in gene or protein sequences", "biscuit_align": "Aligns single- or paired-end reads from bisulfite-converted libraries to a reference genome using Biscuit.", "wgsim": "simulating sequence reads from a reference genome", "agrvate": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants", "gatk4_mergevcfs": "Merges several vcf files"}}, "target": "wgsim", "target_idx": 2}
{"id": "mod_gatk4spark_applybqsr_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Apply base quality score recalibration (BQSR) to a bam file (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4spark/applybqsr": "Apply base quality score recalibration (BQSR) to a bam file", "ucsc/bedclip": "Remove lines from bed file that refer to off-chromosome locations.", "atlas/pmd": "Estimate the post-mortem damage patterns of DNA", "ascat": "copy number profiles of tumour cells.", "resfinder/run": "ResFinder identifies acquired antimicrobial resistance genes in total or partial sequenced isolates of bacteri"}}, "target": "gatk4spark/applybqsr", "target_idx": 0}
{"id": "mod_taxpasta_merge_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Standardise and merge two or more taxonomic profiles into a single table (tools: taxpasta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"taxpasta/merge": "Standardise and merge two or more taxonomic profiles into a single table", "glnexus": "merge gVCF files and perform joint variant calling", "bracken/bracken": "Re-estimate taxonomic abundance of metagenomic samples analyzed by kraken.", "argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD).", "narfmap/hashtable": "Create DRAGEN hashtable for reference genome"}}, "target": "taxpasta/merge", "target_idx": 0}
{"id": "pipe_all101_cutandrun_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak calling and downstream analysis.. Topics: cutandrun, cutandrun-seq, cutandtag, cutandtag-seq. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"denovotranscript": "A pipeline for de novo transcriptome assembly of paired-end short reads from bulk RNA-seq [denovo-assembly, rna-seq, tra", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline [atac-seq, chromatin-accessibiity]", "kmermaid": " k-mer similarity analysis pipeline [k-mer, kmer, kmer-counting]", "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"}}, "target": "cutandrun", "target_idx": 4}
{"id": "samplesheet_arch_metatranscriptome_denovo_0_2", "category": "samplesheet_schema", "state": {"assay": "Environmental community metatranscriptomics de novo assembly", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Environmental community metatranscriptomics de novo assembly?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,environment": null, "sample,rrna_fasta": null}}, "target": "sample,fastq_1,fastq_2,environment", "target_idx": 2}
{"id": "noul_invalid_process_communication_via_globals_19", "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": "qc_adapt_pe_illumina_fastqc_0_25", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_3_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": "Define the required samplesheet CSV header schema for Hybrid bacterial assembly combining short Illumina and long Nanopore reads with entry step FASTQC.", "criteria": {"sample,bam": null, "sample,fasta": null, "sample,fastq_1,fastq_2,long_fastq": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 2}
{"id": "mod_graphtyper_genotype_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Tools for population-scale genotyping using pangenome graphs. (tools: graphtyper)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ferrohgvs/parse": "Parse and validate HGVS variant descriptions with ferro", "graphtyper/genotype": "Tools for population-scale genotyping using pangenome graphs.", "graphtyper/vcfconcatenate": "Tools for population-scale genotyping using pangenome graphs.", "traitar/pfamget": "Download PFAM database for traitar phenotype prediction", "cadd": "CADD is a tool for scoring the deleteriousness of single nucleotide variants as well as insertion/deletions va"}}, "target": "graphtyper/genotype", "target_idx": 1}
{"id": "local_subworkflow_prepontreads_2_5", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPONTREADS", "modules": ["porechop", "nanoplot"], "description": "Nanopore adapter trimming and read quality visualization"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for PREPONTREADS (porechop, nanoplot).", "criteria": {"Local subworkflow PREPONTREADS": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow prepontreads": null, "Leave them out": null}}, "target": "Local subworkflow PREPONTREADS", "target_idx": 0}
{"id": "core_tool_picard_markduplicates_described_2", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Identify and flag PCR and optical duplicate reads in coordinate-sorted BAM files based on 5-prime mapping coordinates.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"fastp": "FASTQ trimmer", "picard_markduplicates": "Identifies duplicate reads in BAM files", "samtools": "SAM/BAM utilities", "gatk_markduplicates": "GATK duplicate marking", "sambamba": "Fast BAM tools"}}, "target": "picard_markduplicates", "target_idx": 1}
{"id": "resource_bracken_bracken_3", "category": "resource_profiling", "state": {"process": "BRACKEN_BRACKEN", "tool": "bracken/bracken", "description": "Re-estimate taxonomic abundance of metagenomic samples analyzed by kraken."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BRACKEN_BRACKEN (Re-estimate taxonomic abundance of metagenomic samples analyzed by kraken.) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_svtools_vcftobedpe_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert a VCF file to a BEDPE file. (tools: svtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_mpileup": "Compresses VCF files", "svtools_vcftobedpe": "Convert a VCF file to a BEDPE file.", "pbsv_discover": "pbsv - PacBio structural variant (SV) signature discovery tool", "last_mafconvert": "Converts MAF alignments in another format.", "delly_call": "Call structural variants"}}, "target": "svtools_vcftobedpe", "target_idx": 1}
{"id": "mod_parabricks_starfusion_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: This tool uses the GPU to perform fusion calling for RNA-Seq samples, utilizing the STAR-Fusion algorithm. This requires input of a genome resource library, in accordance with the original STAR-Fusion tool, and outputs candidate fusion transcripts. (tools: parabricks)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"arriba_arriba": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data.", "fusioninspector": "Validation of Fusion Transcript Predictions", "rundbcan_database": "command from run_dbcan to prepare the database for dbCAN annotation.", "parabricks_starfusion": "This tool uses the GPU to perform fusion calling for RNA-Seq samples, utilizing the STAR-Fusion algorithm. Thi", "custom_sratoolsncbisettings": "Test for the presence of suitable NCBI settings or create them on the fly."}}, "target": "parabricks_starfusion", "target_idx": 3}
{"id": "pipe_all101_proteinfamilies_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Generation and updating of protein families. Topics: metagenomics, protein-families. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"kmermaid": " k-mer similarity analysis pipeline [k-mer, kmer, kmer-counting]", "coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]", "proteinfamilies": "Generation and updating of protein families [metagenomics, protein-families]", "hlatyping": "Precision HLA typing from next-generation sequencing data [dna, hla, hla-typing]", "viralmetagenome": "A nf-core pipeline for untargeted whole genome reconstruction with iSNV detection from metagenomic samples.  [epidemiolo"}}, "target": "proteinfamilies", "target_idx": 2}
{"id": "noul_invalid_process_communication_via_globals_6", "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_nonpareil_nonpareil_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate metagenome redundancy curve from FASTQ files (tools: nonpareil)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amps": null, "argnorm": null, "nonpareil_nonpareil": null, "cnvkit_export": null, "blast_makeblastdb": null}}, "target": "nonpareil_nonpareil", "target_idx": 2}
{"id": "core_tool_samtools_described_0", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Coordinate-sorting, indexing, and statistics generation for genome-aligned BAM binary alignment files.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"bedtools": "Genomic arithmetic tools", "sambamba": "Fast BAM manipulation", "samtools": "Reading/writing/sorting/indexing/viewing SAM/BAM/CRAM format alignments", "picard": "Java-based BAM utilities", "bamtools": "C++ API and toolkit for BAM"}}, "target": "samtools", "target_idx": 2}
{"id": "resource_bamutil_clipoverlap_1", "category": "resource_profiling", "state": {"process": "BAMUTIL_CLIPOVERLAP", "tool": "bamutil/clipoverlap", "description": "clips overlapping read pairs. When two mates overlap, this tool will clip the record's whose clipped region would have the lowest average quality."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMUTIL_CLIPOVERLAP (clips overlapping read pairs. When two mates overlap, this tool will clip the re) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_bulk_rnaseq_pe_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/rnaseq --input samplesheet.csv (Assay: Paired-end Illumina RNA-seq with strandedness)", "question": {"type": "choice", "instructions": "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": "mod_circexplorer2_parse_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: CIRCexplorer2 parses fusion junction files from multiple aligners to prepare them for CIRCexplorer2 annotate. (tools: circexplorer2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"segemehl/index": "Generate genome indices for segemehl align", "ciri2": "Circular RNA identification based on multiple seed matching", "links": "LINKS is a genomics application for scaffolding genome assemblies with long reads,\nsuch as those produced by O", "circexplorer2/parse": "CIRCexplorer2 parses fusion junction files from multiple aligners to prepare them for CIRCexplorer2 annotate.", "gatk4/variantfiltration": "Filter variants"}}, "target": "circexplorer2/parse", "target_idx": 3}
{"id": "resource_bakta_bakta_1", "category": "resource_profiling", "state": {"process": "BAKTA_BAKTA", "tool": "bakta/bakta", "description": "Annotation of bacterial genomes (isolates, MAGs) and plasmids"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAKTA_BAKTA (Annotation of bacterial genomes (isolates, MAGs) and plasmids) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "pipe_all101_viralintegration_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Analysis pipeline for the identification of viral integration events in genomes using a chimeric read approach.. Topics: chimeric-alignment, ctat, viral-integration, virus, virusintegrationfinder. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"bacass": "Simple bacterial assembly and annotation pipeline [assembly, bacterial-genomes, denovo]", "molkart": "A pipeline for processing Molecular Cartography data from Resolve Bioscience (combinatorial FISH) [fish, image-processin", "viralintegration": "Analysis pipeline for the identification of viral integration events in genomes using a chimeric read approach. [chimeri", "nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]", "createtaxdb": "Parallelised and automated construction of metagenomic classifier databases of different tools [database, database-build"}}, "target": "viralintegration", "target_idx": 2}
{"id": "mod_quilt_quilt2_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: QUILT2 is an R and C++ program for fast genotype imputation from low-coverage sequence using a large phased reference panel in VCF/BCF format. (tools: quilt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tcoffee/seqreformat": "Reformats files with t-coffee", "glimpse/ligate": "Concatenates imputation chunks in a single VCF/BCF file ligating phased information.", "quilt/quilt2": "QUILT2 is an R and C++ program for fast genotype imputation from low-coverage sequence using a large phased re", "glimpse/phase": "main GLIMPSE algorithm, performs phasing and imputation refining genotype likelihoods", "glimpse2/phase": "Tool for imputation and phasing from vcf file or directly from bam files."}}, "target": "quilt/quilt2", "target_idx": 2}
{"id": "samplesheet_arch_germline_lane_split_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Multi-lane Illumina sequencing run of clinical samples. Input files: FASTQ files split across flowcell lanes (L001, L002) needing RG alignment.", "question": {"type": "choice", "instructions": "Which columns are standard for Multi-lane Illumina sequencing run of clinical samples input samplesheet?", "criteria": {"sample,bam": null, "lane,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "patient,sample,lane,fastq_1,fastq_2": null}}, "target": "patient,sample,lane,fastq_1,fastq_2", "target_idx": 3}
{"id": "resource_bbmap_bbnorm_2", "category": "resource_profiling", "state": {"process": "BBMAP_BBNORM", "tool": "bbmap/bbnorm", "description": "BBNorm is designed to normalize coverage by down-sampling reads over high-depth areas of a genome, to result in a flat coverage distribution."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_BBNORM (BBNorm is designed to normalize coverage by down-sampling reads over high-depth ) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_rnafusion_pe_0_1", "category": "samplesheet_schema", "state": {"assay": "RNA gene fusion detection (Arriba, STAR-Fusion)", "first_step": "FASTQC", "inputs": "Paired-end oncology RNA-seq reads for chimeric transcript discovery"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: RNA gene fusion detection (Arriba, STAR-Fusion)?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fusion_bed": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 3}
{"id": "samplesheet_arch_cancer_somatic_tn_7_2", "category": "samplesheet_schema", "state": {"technology": "Cancer Genomics", "workflow_entry": "BWA_MEM", "library_inputs": "Paired-end FASTQs for patient tumor and germline normal tissue"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for tumor-normal pairs?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_ichorcna_run_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: ichorCNA is an R package for calculating copy number alteration from (low-pass) whole genome sequencing, particularly for use in cell-free DNA (tools: ichorcna)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cnvkit_antitarget": "Derive off-target (“antitarget”) bins from target regions.", "fgumi_correct": "Correct UMIs in a BAM file to a fixed set of known UMIs with fgumi", "cnvnator_cnvnator": "CNVnator is a command line tool for CNV/CNA analysis from depth-of-coverage by mapped reads.", "ichorcna_run": "ichorCNA is an R package for calculating copy number alteration from (low-pass) whole genome sequencing, parti", "happy_ftxpy": "Somatic VCF Feature Extraction tool from hap.y."}}, "target": "ichorcna_run", "target_idx": 3}
{"id": "samplesheet_arch_prealigned_bam_indexed_3_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Pre-aligned BAM variant calling pipeline. Input files: Aligned BAM files.", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Pre-aligned BAM variant calling pipeline with entry step GATK_HAPLOTYPECALLER.", "criteria": {"sample,bam,bai": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,bam,bai", "target_idx": 0}
{"id": "subworkflow_pkg_vcf_phase_shapeit5_0", "category": "subworkflow_packaging", "state": {"subworkflow": "VCF_PHASE_SHAPEIT5", "modules": ["glimpse2/chunk", "shapeit5/phasecommon", "shapeit5/ligate", "bcftools/index"], "description": "Subworkflow to phase a reference panel VCF file using SHAPEIT5."}, "question": {"type": "choice", "instructions": "How should VCF_PHASE_SHAPEIT5 (glimpse2/chunk, shapeit5/phasecommon, shapeit5/ligate, bcftools/index) be structured in DSL2?", "criteria": {"Local subworkflow VCF_PHASE_SHAPEIT5": null, "Use nf-core subworkflow vcf_phase_shapeit5": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Use nf-core subworkflow vcf_phase_shapeit5", "target_idx": 1}
{"id": "mod_quantmsutils_diann2mztab_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert DIA-NN results to mzTab, MSstats, and Triqler formats using quantms-utils (tools: quantms-utils)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"diann_insilicolibrarygeneration": null, "hifiadapterfilt_hifiadapterfilt": null, "comet": null, "quantmsutils_diann2mztab": null, "anndata_barcodes": null}}, "target": "quantmsutils_diann2mztab", "target_idx": 3}
{"id": "pipe_all101_metatdenovo_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for eukaryotes. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"kmermaid": " k-mer similarity analysis pipeline [k-mer, kmer, kmer-counting]", "airrflow": "B-cell and T-cell Adaptive Immune Receptor Repertoire (AIRR) sequencing analysis pipeline using the Immcantation framewo", "clipseq": "CLIP sequencing analysis pipeline for QC, pre-mapping, genome mapping, UMI deduplication, and multiple peak-calling opti", "metatdenovo": "Assembly and annotation of metatranscriptomic or metagenomic data for prokaryotic, eukaryotic and viruses. [eukaryotes, ", "viralmetagenome": "A nf-core pipeline for untargeted whole genome reconstruction with iSNV detection from metagenomic samples.  [epidemiolo", "createpanelrefs": "Generate Panel of Normals, models or other similar references from lots of samples", "differentialabundance": "Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq  [atac-seq, chip-seq, d", "proteinfamilies": "Generation and updating of protein families [metagenomics, protein-families]", "phyloplace": "nf-core/phyloplace is a bioinformatics best-practice analysis pipeline that performs phylogenetic placement with EPA-NG.", "dualrnaseq": "Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous"}}, "target": "metatdenovo", "target_idx": 3}
{"id": "mod_mobsuite_recon_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool to reconstruct plasmids in bacterial assemblies (tools: mobsuite)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mobsuite_recon": null, "abricate_run": null, "bandage_image": null, "antismash_antismash": null, "biohansel": null}}, "target": "mobsuite_recon", "target_idx": 0}
{"id": "mod_memote_report_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate HTML quality report snapshot for genome-scale metabolic models (tools: memote)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/calculatecontamination": "Calculates the fraction of reads from cross-sample contamination based on summary tables from getpileupsummari", "hipstr": "Genotype and phase short tandem repeats using Illumina whole-genome sequencing data", "memote/report": "Generate HTML quality report snapshot for genome-scale metabolic models", "carveme/carve": "Reconstruct genome-scale metabolic models from protein FASTA files using CarveMe", "gapseq/fill": "Perform gap filling on draft metabolic model"}}, "target": "memote/report", "target_idx": 2}
{"id": "mod_bedtools_slop_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Adds a specified number of bases in each direction (unique values may be specified for either -l or -r) (tools: bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"annotsv_annotsv": "Annotation and Ranking of Structural Variation", "bedops_convert2bed": "Convert BAM/GFF/GTF/GVF/PSL files to bed", "bedtools_slop": "Adds a specified number of bases in each direction (unique values may be specified for either -l or -r)", "trimgalore": "A wrapper around Cutadapt and FastQC to consistently apply adapter and quality trimming to FastQ files,\nwith e", "datavzrd": "Datavzrd is a tool to create visual HTML reports from collections of CSV/TSV tables."}}, "target": "bedtools_slop", "target_idx": 2}
{"id": "mod_picard_collectrnaseqmetrics_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Collect metrics from a RNAseq BAM file (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fusioncatcher/fusioncatcher": "FusionCatcher searches for novel/known somatic fusion genes, translocations, and chimeras in RNA-seq data", "genotyphi/parse": "Genotype Salmonella Typhi from Mykrobe results", "fastq_align_dedup_bwameth": "Performs alignment of BS-Seq reads using bwameth or parabricks/fq2bammeth, sort and deduplicate", "ctatsplicing/startocancerintrons": "Detection and annotation of aberrant splicing isoforms in cancer transcriptomes", "picard/collectrnaseqmetrics": "Collect metrics from a RNAseq BAM file"}}, "target": "picard/collectrnaseqmetrics", "target_idx": 4}
{"id": "mod_juicertools_pre_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create a multi-resolution .hic contact matrix for analysis with Juicer (tools: juicertools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ldak/kvikstep1": null, "cooler/merge": null, "juicertools/pre": null, "rhocall/annotate": null, "cooler/cload": null}}, "target": "juicertools/pre", "target_idx": 2}
{"id": "qc_adapt_qc_aggregate_1_4", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "mod_samtools_consensus_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Produces a consensus FASTA/FASTQ/PILEUP (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"aardvark/merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF.", "bcftools/split": "Split a vcf file into files per chromosome", "samtools/consensus": "Produces a consensus FASTA/FASTQ/PILEUP", "bismark/coverage2cytosine": "Relates methylation calls back to genomic cytosine contexts.", "utils_nfvalidation_plugin": "Use nf-validation to initiate and validate a pipeline"}}, "target": "samtools/consensus", "target_idx": 2}
{"id": "mod_caalm_caalm_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Annotates carbohydrate-active enzyme (CAZyme) families from protein sequences\nusing protein language model (ESM) embeddings and FAISS-based nearest-neighbour\nsearch. Performs three-level hierarchical classification: binary CAZyme detection\n(Level 0), CAZy class assignment (Level 1), and CAZy family assignment (Level 2). (tools: caalm)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"caalm/downloadmodels": "Downloads the CAALM model weights from HuggingFace Hub (lczong/CAALM) into a\nlocal models/ directory. The down", "vcf_extract_relate_somalier": "Perform somalier extraction and relate stats on input VCFs", "caalm/caalm": "Annotates carbohydrate-active enzyme (CAZyme) families from protein sequences\nusing protein language model (ES", "rundbcan/easycgc": "CGC annotation module for the dbcan pipeline. This module is used to annotate carbohydrate-active enzymes (CAZ", "presto/filterseq": "Filter reads by quality score."}}, "target": "caalm/caalm", "target_idx": 2}
{"id": "qc_adapt_pacbio_hifi_2_48", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "qc_adapt_ffpe_wes_1_37", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "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": "pipe_all101_hlatyping_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Precision HLA typing from next-generation sequencing data. Topics: dna, hla, hla-typing, immunology, optitype, personalized-medicine. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"circdna": "Pipeline for the identification of extrachromosomal circular DNA (ecDNA) from Circle-seq, WGS, and ATAC-seq data that we", "createtaxdb": "Parallelised and automated construction of metagenomic classifier databases of different tools [database, database-build", "denovotranscript": "A pipeline for de novo transcriptome assembly of paired-end short reads from bulk RNA-seq [denovo-assembly, rna-seq, tra", "rnasplice": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis [alternative-splicing, rna, rna-seq]", "hlatyping": "Precision HLA typing from next-generation sequencing data [dna, hla, hla-typing]", "lsmquant": "A pipeline for processing and analysis of light-sheet microscopy images. [3dunet, image-analysis, image-processing]", "fastquorum": "Pipeline to produce consensus reads using unique molecular indexes/barcodes (UMIs) [consensus, umi, umis]", "variantbenchmarking": "Pipeline to evaluate and validate the accuracy of variant calling methods in genomic research [benchmark, small-variants", "pathogensurveillance": "Surveillance of pathogens using population genomics and sequencing [biosurveillance, pathogen-identification]", "raredisease": "Call and score variants from WGS/WES of rare disease patients. [diagnostics, rare-disease, snv]"}}, "target": "hlatyping", "target_idx": 4}
{"id": "mod_cdhit_cdhit_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Cluster protein sequences using sequence similarity (tools: cdhit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bftools/showinf": null, "cdhit/cdhit": null, "scds": null, "galah": null, "isoseq/cluster": null}}, "target": "cdhit/cdhit", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_2_1", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "local_subworkflow_positionsofint_2_1", "category": "subworkflow_packaging", "state": {"subworkflow": "POSITIONSOFINT", "modules": ["custom/positionsofint"], "description": "Position of interest depth extraction"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for POSITIONSOFINT (custom/positionsofint).", "criteria": {"Local subworkflow POSITIONSOFINT": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow positionsofint": null, "Leave them out": null}}, "target": "Local subworkflow POSITIONSOFINT", "target_idx": 0}
{"id": "pipe_all101_lsmquant_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for 3dunet analysis? Specific context: A pipeline for processing and analysis of light-sheet microscopy images.. Topics: 3dunet, image-analysis, image-processing, light-sheet-microcopy, segmentation, stitching. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"longraredisease": "Long read sequencing pipeline to identify variants in patients with neurodevelopmental disorders  [nanopore, pacbio]", "mnaseseq": "MNase-seq analysis pipeline using BWA and DANPOS2. [mnase-seq, nucleosome, nucleosome-maps]", "rnavar": "gatk4 RNA variant calling pipeline [gatk4, rna, rnaseq]", "marsseq": "MARS-seq v2 pre-processing pipeline with velocity [facs-sorting, mars-seq, single-cell]", "coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]", "lsmquant": "A pipeline for processing and analysis of light-sheet microscopy images. [3dunet, image-analysis, image-processing]", "variantbenchmarking": "Pipeline to evaluate and validate the accuracy of variant calling methods in genomic research [benchmark, small-variants", "imcyto": "Image Mass Cytometry analysis pipeline [cytometry, image-analysis, image-processing]", "metaboigniter": "Pre-processing of mass spectrometry-based metabolomics data with quantification and identification based on MS1 and MS2 ", "fastquorum": "Pipeline to produce consensus reads using unique molecular indexes/barcodes (UMIs) [consensus, umi, umis]"}}, "target": "lsmquant", "target_idx": 5}
{"id": "subworkflow_pkg_fastq_download_prefetch_fasterqdump_sratools_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_DOWNLOAD_PREFETCH_FASTERQDUMP_SRATOOLS", "modules": ["custom/sratoolsncbisettings", "sratools/prefetch", "sratools/fasterqdump"], "description": "Download FASTQ sequencing reads from the NCBI's Sequence Read Archive (SRA)."}, "question": {"type": "choice", "instructions": "How should FASTQ_DOWNLOAD_PREFETCH_FASTERQDUMP_SRATOOLS (custom/sratoolsncbisettings, sratools/prefetch, sratools/fasterqdump) be structured in DSL2?", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow fastq_download_prefetch_fasterqdump_sratools": null, "Local subworkflow FASTQ_DOWNLOAD_PREFETCH_FASTERQDUMP_SRATOOLS": null}}, "target": "Use nf-core subworkflow fastq_download_prefetch_fasterqdump_sratools", "target_idx": 2}
{"id": "mod_savana_cna_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Copy-number aberration calling with SAVANA for long-read tumour/normal alignments. (tools: savana)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"controlfreec/assesssignificance": "Add both Wilcoxon test and Kolmogorov-Smirnov test p-values to each CNV output of FREEC", "controlfreec/freec2bed": "Plot Freec output", "agat/spfilterfeaturefromkilllist": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID", "savana/cna": "Copy-number aberration calling with SAVANA for long-read tumour/normal alignments.", "crabz/compress": "Compress files with crabz"}}, "target": "savana/cna", "target_idx": 3}
{"id": "mod_parabricks_indexgvcf_0", "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": {"aardvark/merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF.", "bcftools/call": "This command replaces the former bcftools view caller.\nSome of the original functionality has been temporarily", "krakenuniq/build": "Download and build (custom) KrakenUniq databases", "parabricks/indexgvcf": "NVIDIA Clara Parabricks GPU-accelerated gvcf indexing tool.", "bismark/methylationextractor": "Extracts methylation information for individual cytosines from alignments."}}, "target": "parabricks/indexgvcf", "target_idx": 3}
{"id": "samplesheet_arch_cancer_somatic_tn_3_0", "category": "samplesheet_schema", "state": {"assay": "Somatic cancer variant calling with tumor-normal pairs", "first_step": "BWA_MEM"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Somatic cancer variant calling with tumor-normal pairs with entry step BWA_MEM.", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "patient,sample,status,bam,bai": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 0}
{"id": "qc_adapt_ont_ultra_long_2_14", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "qc_adapt_targeted_amplicon_1_32", "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": "intent_ask_question_10", "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": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules"}}, "target": "ask_question", "target_idx": 3}
{"id": "mod_evigene_tr2aacds_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Uses evigene/scripts/prot/tr2aacds.pl to filter a transcript assembly (tools: evigene)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gmmdemux": "GMM-Demux is a Gaussian-Mixture-Model-based software for processing sample barcoding data (cell hashing and MU", "evigene_tr2aacds": "Uses evigene/scripts/prot/tr2aacds.pl to filter a transcript assembly", "agat_spfilterfeaturefromkilllist": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID", "agat_spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "fastq_preprocess_seqkit": "Subworkflow that preprocesses FASTQ files"}}, "target": "evigene_tr2aacds", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_0_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": "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": "resource_abacas_1", "category": "resource_profiling", "state": {"process": "ABACAS", "tool": "abacas", "description": "Contiguate draft genome assembly"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ABACAS (Contiguate draft genome assembly) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "local_subworkflow_variantsofint_1_3", "category": "subworkflow_packaging", "state": {"subworkflow": "VARIANTSOFINT", "modules": ["custom/variantsofint"], "description": "Variant filtering and clinical annotation aggregation"}, "question": {"type": "choice", "instructions": "How should this step (custom/variantsofint) be packaged: Variant filtering and clinical annotation aggregation?", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow VARIANTSOFINT": null, "Use nf-core subworkflow variantsofint": null}}, "target": "Local subworkflow VARIANTSOFINT", "target_idx": 2}
{"id": "resource_bamtofastq10x_4", "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_medium": null, "process_high": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_ancient_dna_eager_0_2", "category": "samplesheet_schema", "state": {"assay": "Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null, "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": "qc_adapt_singlecell_multiqc_0_13", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "resource_bcftools_pluginfilltags_5", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINFILLTAGS", "tool": "bcftools/pluginfilltags", "description": "Compute and fill various INFO tags"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINFILLTAGS (Compute and fill various INFO tags) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "resource_busco_busco_3", "category": "resource_profiling", "state": {"process": "BUSCO_BUSCO", "tool": "busco/busco", "description": "Benchmarking Universal Single Copy Orthologs"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BUSCO_BUSCO (Benchmarking Universal Single Copy Orthologs) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_pycoqc_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: write your description here (tools: pycoqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sentieon/readwriter": "Merges BAM files, and/or convert them into cram files. Also, outputs the result of applying the Base Quality S", "busco/generateplot": "BUSCO plot generation tool", "pycoqc": "write your description here", "busco/download": "Download database for BUSCO", "biscuit/qc": "Perform basic quality control on a BAM file generated with Biscuit"}}, "target": "pycoqc", "target_idx": 2}
{"id": "schema_std_drop_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/drop", "assay": "drop pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/drop (Pipeline to find aberrant events in RNA-Seq data, useful for)?", "criteria": {"id,samplesheet,lane,flowcell,per_flowcell_manifest": null, "sample,fastq_1,fastq_2,batch,condition": null, "RNA_ID,RNA_BAM_FILE,RNA_BAI_FILE,DNA_ID,DNA_VCF_FILE": null, "patient,sample,fastq_1,fastq_2,bam": null}}, "target": "RNA_ID,RNA_BAM_FILE,RNA_BAI_FILE,DNA_ID,DNA_VCF_FILE", "target_idx": 2}
{"id": "noul_channel_filter_operator_8", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.filter { meta, fastq -> meta.single_end }` filters items based on a boolean closure condition.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_ont_ultra_long_2_35", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_qualimap_rnaseq_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Evaluate alignment data (tools: qualimap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"chelae/trim": "Adapter and quality trimming of short-read FASTQ data using chelae.", "pharmcat/phenotyper": "The PharmCAT Phenotyper is a core module of the Pharmacogenomics Clinical Annotation Tool\nthat translates pati", "pureclip": "PureCLIP is a tool to detect protein-RNA interaction footprints from single-nucleotide CLIP-seq data, such as ", "qualimap/rnaseq": "Evaluate alignment data", "busco/plot": "BUSCO summary plot generation using the built-in 'busco --plot' command"}}, "target": "qualimap/rnaseq", "target_idx": 3}
{"id": "mod_spaceranger_mkref_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module to build the reference needed by the 10x Genomics Space Ranger tool. Uses the spaceranger mkref command. (tools: spaceranger)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bowtie_build": "Create bowtie index for reference genome", "gatk4_cleansam": "Cleans the provided BAM, soft-clipping beyond-end-of-reference alignments and setting MAPQ to 0 for unmapped r", "spaceranger_mkref": "Module to build the reference needed by the 10x Genomics Space Ranger tool. Uses the spaceranger mkref command", "emboss_revseq": "the revseq program from emboss reverse complements a nucleotide sequence", "arriba_download": "Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data."}}, "target": "spaceranger_mkref", "target_idx": 2}
{"id": "mod_fastq_removeadapters_merge_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Remove adapters and merge reads based on various module choices (tools: fastq_removeadapters_merge)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastq_removeadapters_merge": "Remove adapters and merge reads based on various module choices", "trimgalore": "A wrapper around Cutadapt and FastQC to consistently apply adapter and quality trimming to FastQ files,\nwith e", "canu": "Accurate assembly of segmental duplications, satellites, and allelic variants from high-fidelity long reads.", "fastq_trim_fastp_fastqc": "Read QC, fastp trimming and read qc", "deepvariant_callvariants": "Call variants from the examples produced by make_examples"}}, "target": "fastq_removeadapters_merge", "target_idx": 0}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_8_0", "category": "samplesheet_schema", "state": {"assay": "PacBio HiFi unaligned BAM variant calling", "first_step": "PBMM2_ALIGN", "inputs": "Native unaligned PacBio Sequel IIe / Revio BAM containing kinetics and qualities", "pipeline": "nf-core/pacvar"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for BAM inputs?", "criteria": {"sample,bam": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null}}, "target": "sample,bam", "target_idx": 0}
{"id": "samplesheet_arch_cancer_longitudinal_6_4", "category": "samplesheet_schema", "state": {"assay": "Longitudinal cancer monitoring across multiple timepoints", "first_step": "FASTQC", "inputs": "Serial plasma cfDNA and biopsy FASTQs across treatment intervals", "pipeline": "nf-core/oncoanalyser"}, "question": {"type": "choice", "instructions": "Which columns are standard for Longitudinal cancer monitoring across multiple timepoints input samplesheet?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "patient,sample,timepoint,status,fastq_1,fastq_2": null, "sample,timepoint,fastq": null, "sample,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,status,fastq_1,fastq_2", "target_idx": 1}
{"id": "field_constraint_sample_2_1", "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, "enum: [0, 1]": null, "type: integer": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 0}
{"id": "field_constraint_fastq_1_2_13", "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+\\.bam$": null, "type: integer": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 3}
{"id": "core_tool_bwa_mem_bare_1", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Fast short-read DNA sequence alignment against reference genome creating sorted SAM/BAM alignments for variant calling.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"salmon": null, "bowtie2": null, "star": null, "bwa_mem": null, "minimap2": null}}, "target": "bwa_mem", "target_idx": 3}
{"id": "subworkflow_pkg_fastq_align_bowtie2_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_BOWTIE2", "modules": ["bowtie2/align", "samtools/sort", "samtools/index", "samtools/stats", "samtools/idxstats", "samtools/flagstat", "bam_sort_stats_samtools"], "description": "Align reads to a reference genome using bowtie2 then sort with samtools"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_BOWTIE2 (bowtie2/align, samtools/sort, samtools/index, samtools/stats, samtools/idxstats, samtools/flagstat, bam_sort_stats_samtools) be structured in DSL2?", "criteria": {"Leave them out": null, "Use nf-core subworkflow fastq_align_bowtie2": null, "Keep the modules in the main workflow": null, "Local subworkflow FASTQ_ALIGN_BOWTIE2": null}}, "target": "Use nf-core subworkflow fastq_align_bowtie2", "target_idx": 1}
{"id": "field_constraint_expected_cells_1_7", "category": "samplesheet_schema", "state": {"column": "expected_cells", "purpose": "Expected cell count in single-cell droplet pipelines"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'expected_cells' (Expected cell count in single-cell droplet pipelines).", "criteria": {"format: file-path": null, "enum: [auto, single, paired]": null, "type: integer, minimum: 100, maximum: 50000": null, "pattern: ^\\S+\\.csv$": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 2}
{"id": "qc_adapt_illumina_novaseq_0_12", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "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": "pipe_all101_genomeassembler_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads. Topics: genome-assembly. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"bacass": null, "pathogensurveillance": null, "demultiplex": null, "fastquorum": null, "proteinfamilies": null, "viralintegration": null, "clipseq": null, "fetchngs": null, "genomeassembler": null, "riboseq": null}}, "target": "genomeassembler", "target_idx": 8}
{"id": "resource_biscuit_epiread_3", "category": "resource_profiling", "state": {"process": "BISCUIT_EPIREAD", "tool": "biscuit/epiread", "description": "Summarizes read-level methylation (and optionally SNV) information from a\nBiscuit BAM file in a standard-compliant BED format."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_EPIREAD (Summarizes read-level methylation (and optionally SNV) information from a\nBiscui) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_metagenome_mag_grouped_4_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/mag", "assay_type": "Metagenomic MAG assembly with comparative groups", "data_format": "Paired-end environmental metagenomic FASTQs annotated by environmental cohort/group"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end environmental metagenomic FASTQs annotated by environmental cohort/group?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fasta": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 3}
{"id": "mod_aria2_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: CLI Download utility (tools: aria2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"aria2": null, "ngscheckmate_patterngenerator": null, "annotsv_installannotations": null, "hmmer_eslsfetch": null, "bigslice_downloaddb": null}}, "target": "aria2", "target_idx": 0}
{"id": "resource_abricate_run_2", "category": "resource_profiling", "state": {"process": "ABRICATE_RUN", "tool": "abricate/run", "description": "Screen assemblies for antimicrobial resistance against multiple databases"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ABRICATE_RUN (Screen assemblies for antimicrobial resistance against multiple databases) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "schema_std_datasync_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/datasync", "description": "nf-core/datasync is a system operation pipeline that provides several workflows for handling system operation / automation tasks", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/datasync?", "criteria": {"sample,input,output_path,checksum_md5,checksum_sha": null, "id,test_vcf,test_regions,caller,subsample": null, "sample,fastq_1,fastq_2,replicate,control": null, "id,fasta,query": null}}, "target": "sample,input,output_path,checksum_md5,checksum_sha", "target_idx": 0}
{"id": "qc_adapt_ont_ultra_long_1_1", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "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": "subworkflow_pkg_vcf_gather_bcftools_3", "category": "subworkflow_packaging", "state": {"subworkflow": "VCF_GATHER_BCFTOOLS", "modules": ["bcftools/sort", "bcftools/concat", "htslib/bgziptabix"], "description": "Concatenate several VCF files using bcftools concat."}, "question": {"type": "choice", "instructions": "How should VCF_GATHER_BCFTOOLS (bcftools/sort, bcftools/concat, htslib/bgziptabix) be structured in DSL2?", "criteria": {"Local subworkflow VCF_GATHER_BCFTOOLS": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow vcf_gather_bcftools": null}}, "target": "Use nf-core subworkflow vcf_gather_bcftools", "target_idx": 3}
{"id": "samplesheet_arch_spatial_visium_0_1", "category": "samplesheet_schema", "state": {"assay": "10x Visium spatial transcriptomics with histology image", "first_step": "FASTQC", "inputs": "Spatial cDNA FASTQs paired with high-resolution brightfield tissue image and slide coordinates"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: 10x Visium spatial transcriptomics with histology image?", "criteria": {"sample,bam": null, "sample,image": null, "sample,fastq_1,fastq_2,image,slide,area": null, "sample,fastq_1,image": null}}, "target": "sample,fastq_1,fastq_2,image,slide,area", "target_idx": 2}
{"id": "mod_agat_spkeeplongestisoform_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filters GFF records to keep only the longest isoform per gene (tools: agat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/convertbed2gff": "Takes a bed12 file and converts to a GFF3 file", "xz/compress": "Compresses files with xz.", "agat/convertspgff2tsv": "Converts a GFF/GTF file into a TSV file", "agat/spkeeplongestisoform": "Filters GFF records to keep only the longest isoform per gene", "seqkit/sort": "Sorts sequences by id/name/sequence/length"}}, "target": "agat/spkeeplongestisoform", "target_idx": 3}
{"id": "qc_adapt_illumina_novaseq_0_47", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "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_fgumi_codec_0", "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": {"samtools/faidx": null, "fgumi/downsample": null, "repeatmodeler/builddatabase": null, "fgumi/codec": null, "fgumi/dedup": null}}, "target": "fgumi/codec", "target_idx": 3}
{"id": "mod_rhocall_viz_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Call regions of homozygosity and make tentative UPD calls (tools: rhocall)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_annotate": "Add or remove annotations.", "scramble_clusteridentifier": "The cluster_identifier tool of Scramble identifies soft clipped clusters", "vsearch_dereplicate": "Merge strictly identical sequences contained in filename. Identical sequences are defined as having the same l", "rhocall_annotate": "Markup VCF file using rho-calls.", "rhocall_viz": "Call regions of homozygosity and make tentative UPD calls"}}, "target": "rhocall_viz", "target_idx": 4}
{"id": "noul_channel_join_operator_6", "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_bedtools_map_1", "category": "resource_profiling", "state": {"process": "BEDTOOLS_MAP", "tool": "bedtools/map", "description": "Allows one to screen for overlaps between two sets of genomic features."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_MAP (Allows one to screen for overlaps between two sets of genomic features.) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_vcf_gather_bcftools_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Concatenate several VCF files using bcftools concat.\nAn additional option can be given to sort the concatenated VCF. (tools: vcf_gather_bcftools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tabix_tabix": "DEPRECATED. Use HTSLIB/BGZIPTABIX instead. Create a tabix index from a sorted\nbgzip TAB-delimited genome file,", "deseq2_differential": "runs a differential expression analysis with DESeq2", "annotsv_annotsv": "Annotation and Ranking of Structural Variation", "vcf_gather_bcftools": "Concatenate several VCF files using bcftools concat.\nAn additional option can be given to sort the concatenate", "bcftools_concat": "Concatenate VCF files"}}, "target": "vcf_gather_bcftools", "target_idx": 3}
{"id": "local_subworkflow_prepilluminareads_2_4", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPILLUMINAREADS", "modules": ["trimmomatic"], "description": "Single-step adapter trimming for Illumina reads"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for PREPILLUMINAREADS (trimmomatic).", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow prepilluminareads": null, "Leave them out": null, "Local subworkflow PREPILLUMINAREADS": null}}, "target": "Local subworkflow PREPILLUMINAREADS", "target_idx": 3}
{"id": "intent_prepare_data_5", "category": "intent_routing", "state": "Classify this user request: \"Generate a script to parse our SRA run table and stage paired-end FASTQ downloads for Nextflow.\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"build_pipeline": null, "debug_error": null, "ask_question": null, "prepare_data": null}}, "target": "prepare_data", "target_idx": 3}
{"id": "mod_seqkit_grep_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Select sequences from a large file based on name/ID (tools: seqkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samtools_bam2fq": "The module uses bam2fq method from samtools to\nconvert a SAM, BAM or CRAM file to FASTQ format", "seqkit_grep": "Select sequences from a large file based on name/ID", "bbmap_filterbyname": "Filter out sequences by sequence header name(s)", "bbmap_bbmerge": "Merging overlapping paired reads into a single read.", "agat_spkeeplongestisoform": "Filters GFF records to keep only the longest isoform per gene"}}, "target": "seqkit_grep", "target_idx": 1}
{"id": "mod_getorganelle_config_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Downloads databases needed for running getorganelle (tools: getorganelle)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"truvari/segment": "Normalization of SVs into disjointed genomic regions", "canvas/germline": "Calls germline copy number variants (CNVs) from whole genome sequencing data using\nIllumina Canvas in SmallPed", "getorganelle/config": "Downloads databases needed for running getorganelle", "abyss/abysspe": "ABySS is a de novo sequence assembler intended for short paired-end reads and genomes of all sizes.", "abricate/run": "Screen assemblies for antimicrobial resistance against multiple databases"}}, "target": "getorganelle/config", "target_idx": 2}
{"id": "pipe_all101_rnasplice_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for alternative-splicing. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rnafusion": "RNA-seq analysis pipeline for detection of gene-fusions [fusion, fusion-genes, gene-fusion]", "metatdenovo": "Assembly and annotation of metatranscriptomic or metagenomic data for prokaryotic, eukaryotic and viruses. [eukaryotes, ", "mcmicro": "An end-to-end processing pipeline that transforms multi-channel whole-slide images into single-cell data. [bioformats, i", "rnasplice": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis [alternative-splicing, rna, rna-seq]", "oncoanalyser": "A comprehensive cancer DNA/RNA analysis and reporting pipeline [cancer, clinical, ctdna]", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "drop": "Pipeline to find aberrant events in RNA-Seq data, useful for diagnosis of rare disorders", "crisprseq": "A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments u", "rnavar": "gatk4 RNA variant calling pipeline [gatk4, rna, rnaseq]", "bamtofastq": "Converts bam or cram files to fastq format and does quality control. [bamtofastq, conversion, cramtofastq]"}}, "target": "rnasplice", "target_idx": 3}
{"id": "samplesheet_arch_atacseq_replicates_2_5", "category": "samplesheet_schema", "state": {"assay": "ATAC-seq chromatin accessibility with biological replicates", "first_step": "FASTQC", "inputs": "Paired-end Tn5 transposed FASTQs across conditions and replicates"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2,replicate": null, "sample,bed": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 1}
{"id": "samplesheet_arch_singlecell_parse_splitseq_5_2", "category": "samplesheet_schema", "state": {"assay": "Parse Biosciences Split-seq combinatorial barcoding", "first_step": "FASTQC", "inputs": "Combinatorial split-pool barcoded FASTQs with subpool annotations", "pipeline": "nf-core/scrnaseq"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/scrnaseq, determine the input samplesheet column structure for: Parse Biosciences Split-seq combinatorial barcoding.", "criteria": {"sample,subpool,fastq_1,fastq_2": null, "sample,well,plate": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,subpool,fastq_1,fastq_2", "target_idx": 0}
{"id": "resource_bedtools_slop_5", "category": "resource_profiling", "state": {"process": "BEDTOOLS_SLOP", "tool": "bedtools/slop", "description": "Adds a specified number of bases in each direction (unique values may be specified for either -l or -r)"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_SLOP (Adds a specified number of bases in each direction (unique values may be specifi) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "qc_adapt_pacbio_hifi_1_5", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_gatk4_intervallisttobed_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts an Picard IntervalList file to a BED file. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"entrezdirect/esearch": "Searches a term in a public NCBI database", "annotsv/annotsv": "Annotation and Ranking of Structural Variation", "agat/convertbed2gff": "Takes a bed12 file and converts to a GFF3 file", "gatk4/intervallisttobed": "Converts an Picard IntervalList file to a BED file.", "glimpse/ligate": "Concatenates imputation chunks in a single VCF/BCF file ligating phased information."}}, "target": "gatk4/intervallisttobed", "target_idx": 3}
{"id": "samplesheet_arch_methylseq_bisulfite_0_4", "category": "samplesheet_schema", "state": {"technology": "Epigenomics", "workflow_entry": "FASTQC", "library_inputs": "Bisulfite-converted or enzymatic methyl-converted paired-end FASTQs"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Whole-Genome Bisulfite Sequencing (WGBS / EM-seq)?", "criteria": {"sample,bam": null, "sample,cpg,methylation": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "qc_adapt_pe_illumina_fastqc_0_44", "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_cageseq_transcription_2_5", "category": "samplesheet_schema", "state": {"assay": "CAGE-seq 5-prime capped transcript end sequencing", "first_step": "FASTQC", "inputs": "Single-end capped 5-prime cDNA tags for transcription start site (TSS) mapping"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,vcf": null, "sample,tss_bed": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "mod_mirtop_gff_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: mirtop gff generates the GFF3 adapter format to capture miRNA variations (tools: mirtop)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mirdeep2_mirdeep2": null, "multivcfanalyzer": null, "mirtop_gff": null, "pypgx_runngspipeline": null, "mirtop_counts": null}}, "target": "mirtop_gff", "target_idx": 2}
{"id": "samplesheet_arch_rnafusion_pe_1_3", "category": "samplesheet_schema", "state": {"assay": "RNA gene fusion detection (Arriba, STAR-Fusion)", "first_step": "FASTQC", "inputs": "Paired-end oncology RNA-seq reads for chimeric transcript discovery"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for RNA gene fusion detection (Arriba, STAR-Fusion)?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fusion_bed": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 1}
{"id": "subworkflow_pkg_bed_scatter_bedtools_2", "category": "subworkflow_packaging", "state": {"subworkflow": "BED_SCATTER_BEDTOOLS", "modules": ["bedtools/split"], "description": "Scatters inputted BED files by the amount specified."}, "question": {"type": "choice", "instructions": "How should BED_SCATTER_BEDTOOLS (bedtools/split) be structured in DSL2?", "criteria": {"Local subworkflow BED_SCATTER_BEDTOOLS": null, "Use nf-core subworkflow bed_scatter_bedtools": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow bed_scatter_bedtools", "target_idx": 1}
{"id": "pipe_core10_mag_0_described", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? De novo assembly and binning of metagenomic contigs across short and long reads into Metagenome-Assembled Genomes.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 (16s, 18s, amplicon-sequencing, edna)", "chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. (chip, chip-seq, chromatin-immunoprecipitation, macs2)", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples (amplicon, artic, assembly, covid-19)", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data (classification, illumina", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline (atac-seq, chromatin-accessibiity)", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline (adna, ancient-dna-analysis, ancientdna, genome)", "mag": "Assembly and binning of metagenomes (annotation, assembly, binning, long-read-sequencing)", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr"}}, "target": "mag", "target_idx": 8}
{"id": "samplesheet_arch_cancer_somatic_tn_0_4", "category": "samplesheet_schema", "state": {"technology": "Cancer Genomics", "workflow_entry": "BWA_MEM", "library_inputs": "Paired-end FASTQs for patient tumor and germline normal tissue"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Somatic cancer variant calling with tumor-normal pairs?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 2}
{"id": "samplesheet_arch_faire_seq_chromatin_0_0", "category": "samplesheet_schema", "state": {"assay": "FAIRE-seq / DNAse-seq open chromatin profiling", "first_step": "FASTQC", "inputs": "Formaldehyde-assisted isolation of regulatory elements paired-end FASTQs", "pipeline": "nf-core/atacseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: FAIRE-seq / DNAse-seq open chromatin profiling?", "criteria": {"sample,bed": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam,bai": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "qc_adapt_ont_ultra_long_1_12", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_plink2_het_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate Inbreeding data with plink2 (tools: plink2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink2_remove": null, "sentieon_bwamem": null, "plink2_indeppairwise": null, "pbtk_bam2fastq": null, "plink2_het": null}}, "target": "plink2_het", "target_idx": 4}
{"id": "mod_bedtools_merge_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: combines overlapping or “book-ended” features in an interval file into a single feature which spans all of the combined features. (tools: bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastq_align_star": null, "ribotricer/prepareorfs": null, "bedtools/merge": null, "agat/convertgff2bed": null, "bamtools/convert": null}}, "target": "bedtools/merge", "target_idx": 2}
{"id": "mod_gatk4_addorreplacereadgroups_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Assigns all the reads in a file to a single new read-group (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"picard_addorreplacereadgroups": "Assigns all the reads in a file to a single new read-group", "macsyfinder_download": "Download MacSyFinder models using msf_data", "phispy": "Predict prophages in bacterial genomes", "gatk4_addorreplacereadgroups": "Assigns all the reads in a file to a single new read-group", "picard_cleansam": "Cleans the provided BAM, soft-clipping beyond-end-of-reference alignments and setting MAPQ to 0 for unmapped r"}}, "target": "gatk4_addorreplacereadgroups", "target_idx": 3}
{"id": "qc_adapt_pe_illumina_fastqc_2_36", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Standard Paired-end Illumina RNA-seq (short_reads_150bp).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_vcf_phase_shapeit5_0", "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": {"vcf_phase_shapeit5": null, "bcftools/annotate": null, "deeptools/plotheatmap": null, "annotsv/annotsv": null, "prokka": null}}, "target": "vcf_phase_shapeit5", "target_idx": 0}
{"id": "samplesheet_arch_mira_influenza_sc2_1_3", "category": "samplesheet_schema", "state": {"assay": "Custom MIRA-NF Influenza / SC2 pipeline", "first_step": "INPUT_CHECK", "inputs": "Paired-end surveillance FASTQs from respiratory pathogen panels"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Custom MIRA-NF Influenza / SC2 pipeline?", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "noul_channel_filter_operator_5", "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": "pipe_all101_hic_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Analysis of Chromosome Conformation Capture data (Hi-C). Topics: chromosome-conformation-capture, hi-c. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"clipseq": "CLIP sequencing analysis pipeline for QC, pre-mapping, genome mapping, UMI deduplication, and multiple peak-calling opti", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "references": "nf-core/references is a bioinformatics pipeline that build references, for multiple use cases [genome, references, repro", "rnastructurome": "a bioinformatics pipeline for analysing chemical high-throughput RNA structure-probing data [dms, map, rna-structure]", "genomeqc": "Compare the quality of multiple genomes, along with their annotations. [genome-assembly-evaluation, genomics, phylogenet", "reportho": "nf-core pipeline for comparative analysis of ortholog predictions [ortholog]", "hic": "Analysis of Chromosome Conformation Capture data (Hi-C) [chromosome-conformation-capture, hi-c]", "seqinspector": "Dedicated QC-only pipeline for sequencing data. The pipeline will run a (potentially large) set of QC tools and can outp"}}, "target": "hic", "target_idx": 6}
{"id": "mod_lofreq_filter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Lofreq subcommand to remove variants with low coverage or strand bias potential (tools: lofreq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools/concat": "Concatenate VCF files", "lofreq/filter": "Lofreq subcommand to remove variants with low coverage or strand bias potential", "bedtools/complement": "Returns all intervals in a genome that are not covered by at least one interval in the input BED/GFF/VCF file.", "bcftools/consensus": "Compresses VCF files", "genmod/models": "annotate models of inheritance"}}, "target": "lofreq/filter", "target_idx": 1}
{"id": "mod_cmseq_polymut_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculates polymorphic site rates over protein coding genes (tools: cmseq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/fastqtosam": null, "cmseq/polymut": null, "vt/normalize": null, "t1k/build": null, "t1k/run": null}}, "target": "cmseq/polymut", "target_idx": 1}
{"id": "samplesheet_arch_cutandrun_pe_5_4", "category": "samplesheet_schema", "state": {"assay": "CUT&RUN / CUT&TAG chromatin profiling with IgG control", "first_step": "FASTQC"}, "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": null, "sample,fastq_1,fastq_2,target,control": null, "sample,spikein,fastq": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 1}
{"id": "intent_prepare_data_24", "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", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules"}}, "target": "prepare_data", "target_idx": 2}
{"id": "mod_s4pred_runmodel_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Prediction of a protein's secondary structure from its amino acid sequence (tools: s4pred)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"blast/blastp": null, "s4pred/runmodel": null, "bcftools/csq": null, "cooler/merge": null, "deepvariant/rundeepvariant": null}}, "target": "s4pred/runmodel", "target_idx": 1}
{"id": "mod_nail_search_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: nail search is a fast and scalable tool for searching protein sequences against protein databases (tools: nail)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamreadcount": null, "amps": null, "alignoth": null, "parabricks/fq2bam": null, "nail/search": null}}, "target": "nail/search", "target_idx": 4}
{"id": "resource_bedtools_unionbedg_4", "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_medium": null, "process_low": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_rtn_tni_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Uses the RTN R package for transcriptional regulatory network inference (TNI). (tools: rtn)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"kat_hist": "Creates a histogram of the number of distinct k-mers having a given frequency.", "rtn_tni": "Uses the RTN R package for transcriptional regulatory network inference (TNI).", "anndata_barcodes": "Module to subset AnnData object to cells with matching barcodes from the csv file", "fq_lint": "fq lint is a FASTQ file pair validator.", "ciri2": "Circular RNA identification based on multiple seed matching"}}, "target": "rtn_tni", "target_idx": 1}
{"id": "mod_foldmason_msa2lddtreport_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Renders a visualization report using foldmason (tools: foldmason)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"alignoth": "Creating alignment plots from bam files", "crumble": "Controllable lossy compression of BAM/CRAM files", "foldmason_msa2lddtreport": "Renders a visualization report using foldmason", "fastq_shortreads_preprocess_qc": "Quality check and preprocessing subworkflow of Illumina short reads\nthat can do: quality check of input reads ", "bwa_mem": "Performs fastq alignment to a fasta reference using BWA"}}, "target": "foldmason_msa2lddtreport", "target_idx": 2}
{"id": "mod_methyldackel_mbias_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generates methylation bias plots from alignments (tools: methyldackel)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ngscheckmate_fastq": "Determining whether sequencing data comes from the same individual by using SNP matching. This module generate", "methyldackel_mbias": "Generates methylation bias plots from alignments", "tiddit_cov": "Computes the coverage of different regions from the bam file.", "bismark_report": "Collects bismark alignment reports", "bismark_align": "Performs alignment of BS-Seq reads using bismark"}}, "target": "methyldackel_mbias", "target_idx": 1}
{"id": "local_subworkflow_daisribosome_0_5", "category": "subworkflow_packaging", "state": {"subworkflow": "DAISRIBOSOME", "modules": ["dais"], "description": "Custom ribosomal frameshift translation analysis"}, "question": {"type": "choice", "instructions": "How should DAISRIBOSOME (dais) be built?", "criteria": {"Local subworkflow DAISRIBOSOME": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow daisribosome": null, "Leave them out": null}}, "target": "Local subworkflow DAISRIBOSOME", "target_idx": 0}
{"id": "noul_named_process_output_emits_14", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Nextflow DSL2 supports multi-channel emission from processes using named emit blocks: `path '*.bam', emit: bam`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_odgi_viz_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Visualize a variation graph in 1D. (tools: odgi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gem2_gemmappability": null, "odgi_stats": null, "odgi_layout": null, "odgi_viz": null, "pbjasmine": null}}, "target": "odgi_viz", "target_idx": 3}
{"id": "mod_mapad_map_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Map short-reads to an indexed reference genome (tools: mapad)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"catpack_download": null, "atlas_pmd": null, "amps": null, "mapad_map": null, "proseg_proseg2baysor": null}}, "target": "mapad_map", "target_idx": 3}
{"id": "qc_adapt_pe_illumina_fastqc_0_12", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_hisat2_build_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Builds HISAT2 index for reference genome (tools: hisat2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bracken_build": "Extends a Kraken2 database to be compatible with Bracken", "custom_tx2gene": "Make a transcript/gene mapping from a GTF and cross-reference with transcript quantifications.", "catpack_prepare": "Creates a CAT_pack database based on input FASTAs", "hisat2_build": "Builds HISAT2 index for reference genome", "cutesv": "structural-variant calling with cutesv"}}, "target": "hisat2_build", "target_idx": 3}
{"id": "samplesheet_arch_cancer_somatic_bam_2_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Somatic tumor-normal calling from pre-aligned BAM files)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"patient,sample,status,bam,bai": null, "sample,bam,bai": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,sample,bam": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 0}
{"id": "mod_fgumi_dedup_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Mark or remove PCR duplicates using UMI information with fgumi (tools: fgumi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"nacho_qc": "NACHO (NAnostring quality Control dasHbOard) is developed for NanoString nCounter data.\nNanoString nCounter da", "fgumi_clip": "Clip overlapping reads in a BAM file with fgumi", "fgumi_codec": "Call CODEC consensus reads from a UMI-grouped BAM with fgumi", "fgumi_dedup": "Mark or remove PCR duplicates using UMI information with fgumi", "pcne": "Estimates plasmid copy number from assembled genome"}}, "target": "fgumi_dedup", "target_idx": 3}
{"id": "mod_pairtools_flip_0", "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/select": "Select pairs according to given condition by options.args", "sequali": "Sequence quality metrics for FASTQ and uBAM files.", "pharmcat/reporter": "The Reporter module is responsible for generating a report with genotype-specific\nexpert-reviewed drug prescri", "pairtools/flip": "Flip pairs to get an upper-triangular matrix", "opt_flip_track_stat": "Off-target probe detection"}}, "target": "pairtools/flip", "target_idx": 3}
{"id": "mod_svanalyzer_svbenchmark_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: SVbenchmark compares a set of “test” structural variants in VCF format to a known truth set (also in VCF format) and outputs estimates of sensitivity and specificity. (tools: svanalyzer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"octopusv_svcf2bed": null, "svanalyzer_svbenchmark": null, "fgbio_groupreadsbyumi": null, "bam_rseqc": null, "variantextractor": null}}, "target": "svanalyzer_svbenchmark", "target_idx": 1}
{"id": "mod_samtools_collate_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: shuffles and groups reads together by their names (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ascat": "copy number profiles of tumour cells.", "sentieon_rsempreparereference": "Prepare a reference genome for RSEM", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files.", "samtools_collate": "shuffles and groups reads together by their names", "wisecondorx_predict": "Find copy number aberrations"}}, "target": "samtools_collate", "target_idx": 3}
{"id": "resource_bamutil_trimbam_4", "category": "resource_profiling", "state": {"process": "BAMUTIL_TRIMBAM", "tool": "bamutil/trimbam", "description": "trims the end of reads in a SAM/BAM file, changing read ends to ‘N’ and quality to ‘!’, or by soft clipping"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMUTIL_TRIMBAM (trims the end of reads in a SAM/BAM file, changing read ends to ‘N’ and quality ) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "pipe_all101_rnavar_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for gatk4 analysis? Specific context: gatk4 RNA variant calling pipeline. Topics: gatk4, rna, rnaseq, variant-calling, worflow. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"pairgenomealign": "Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plo", "rnasplice": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis [alternative-splicing, rna, rna-seq]", "viralmetagenome": "A nf-core pipeline for untargeted whole genome reconstruction with iSNV detection from metagenomic samples.  [epidemiolo", "sopa": "Nextflow version of Sopa - spatial omics pipeline and analysis [segmentation, spatial-omics, spatial-proteomics]", "bamtofastq": "Converts bam or cram files to fastq format and does quality control. [bamtofastq, conversion, cramtofastq]", "stableexpression": "This pipeline is designed to identify the most stable genes in one or more expression datasets (RNA-seq / Microarray). T", "rnavar": "gatk4 RNA variant calling pipeline [gatk4, rna, rnaseq]", "crisprseq": "A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments u", "smrnaseq": "A small-RNA sequencing analysis pipeline [small-rna, smrna-seq]", "demultiplex": "Demultiplexing pipeline for sequencing data [bases2fastq, bcl2fastq, demultiplexing]"}}, "target": "rnavar", "target_idx": 6}
{"id": "qc_adapt_illumina_novaseq_1_14", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "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": "noul_container_environment_specification_12", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"DSL2 `container` directives can specify Docker, Singularity, or Wave containers per process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_fast2q_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A program that counts sequence occurrences in FASTQ files. (tools: 2FAST2Q)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"adapterremovalfixprefix": "Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with", "fasta_bgzip_index_dict_samtools": "Ensure BGZF compression, index, and produce a sequence size summary and a sequence dictionary for each FASTA f", "hmmer_hmmbuild": "create an hmm profile from a multiple sequence alignment", "fast2q": "A program that counts sequence occurrences in FASTQ files.", "art_illumina": "Simulation tool to generate synthetic Illumina next-generation sequencing reads"}}, "target": "fast2q", "target_idx": 3}
{"id": "mod_bamstats_generalstats_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: write your description here (tools: bamstats)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"wisecondorx/predict": "Find copy number aberrations", "bamclipper": "This module is used to clip primer sequences from your alignments.", "deeptools/multibigwigsummary": "Computes the average scores for each of the files in every genomic region", "bamstats/generalstats": "write your description here", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files."}}, "target": "bamstats/generalstats", "target_idx": 3}
{"id": "qc_adapt_bulk_multiqc_1_44", "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": "pipe_all101_viralmetagenome_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze A nf-core pipeline for untargeted whole genome reconstruction with iSNV detection from metagenomic samples.. Topics: epidemiology, fastq, ngs, viral-metagenomics, virology, virus-genomes. . 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", "demultiplex": "Demultiplexing pipeline for sequencing data [bases2fastq, bcl2fastq, demultiplexing]", "viralmetagenome": "A nf-core pipeline for untargeted whole genome reconstruction with iSNV detection from metagenomic samples.  [epidemiolo", "mnaseseq": "MNase-seq analysis pipeline using BWA and DANPOS2. [mnase-seq, nucleosome, nucleosome-maps]", "nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]"}}, "target": "viralmetagenome", "target_idx": 2}
{"id": "samplesheet_arch_cutandrun_pe_7_2", "category": "samplesheet_schema", "state": {"technology": "Epigenomics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end low-input fragment FASTQs with target antibody and IgG negative control"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for ChIP-seq with controls?", "criteria": {"sample,target,control": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,target,control": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 2}
{"id": "noul_retry_errorstrategy_5", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `errorStrategy = 'retry'` directive allows Nextflow to re-execute a failed task up to `maxRetries` times.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_bulk_multiqc_2_21", "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": "field_constraint_phenotype_2_13", "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, "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": "subworkflow_pkg_mafft_align_1", "category": "subworkflow_packaging", "state": {"subworkflow": "MAFFT_ALIGN", "modules": ["mafft/align"], "description": "Prepare channels for running MAFFT/align"}, "question": {"type": "choice", "instructions": "How should MAFFT_ALIGN (mafft/align) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow MAFFT_ALIGN": null, "Use nf-core subworkflow mafft_align": null, "Leave them out": null}}, "target": "Use nf-core subworkflow mafft_align", "target_idx": 2}
{"id": "mod_sentieon_hsmetrics_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Collects hybrid-selection (HS) metrics for a SAM or BAM file. (tools: sentieon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgumi/simplexmetrics": "Collects a suite of metrics to QC simplex (single-strand) UMI sequencing data", "metaphlan3/mergemetaphlantables": "Merges output abundance tables from MetaPhlAn3", "manta/germline": "Manta calls structural variants (SVs) and indels from mapped paired-end sequencing reads. It is optimized for ", "sentieon/hsmetrics": "Collects hybrid-selection (HS) metrics for a SAM or BAM file.", "fgumi/duplexmetrics": "Collects a suite of metrics to QC duplex sequencing data"}}, "target": "sentieon/hsmetrics", "target_idx": 3}
{"id": "qc_adapt_bulk_multiqc_0_38", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For High-throughput bulk WGS multi-sample run, what is the recommended QC default for MultiQC?", "criteria": {"Keep FastQC": null, "Keep MultiQC": null, "Drop MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "field_constraint_fastq_2_0_12", "category": "samplesheet_schema", "state": {"field_name": "fastq_2", "datatype": "conditional_file_pattern", "description": "Path to read 2 FASTQ file for paired-end sequencing"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'fastq_2'?", "criteria": {"type: required string": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null, "enum: [0, 1]": null, "pattern: ^\\S+\\.bam$": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 1}
{"id": "subworkflow_pkg_quantify_pseudo_alignment_1", "category": "subworkflow_packaging", "state": {"subworkflow": "QUANTIFY_PSEUDO_ALIGNMENT", "modules": ["kallisto/quant", "quant_tximport_summarizedexperiment", "salmon/quant"], "description": "Perform quantification with Salmon or Kallisto to produce count tables and SummarizedExperiment objects"}, "question": {"type": "choice", "instructions": "How should QUANTIFY_PSEUDO_ALIGNMENT (kallisto/quant, quant_tximport_summarizedexperiment, salmon/quant) be structured in DSL2?", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow QUANTIFY_PSEUDO_ALIGNMENT": null, "Use nf-core subworkflow quantify_pseudo_alignment": null}}, "target": "Use nf-core subworkflow quantify_pseudo_alignment", "target_idx": 3}
{"id": "noul_mix_operator_async_emission_11", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.mix()` channel operator waits until all source channels have completed before emitting any items.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "field_constraint_bai_2_9", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'bai' (Companion BAM index file) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'bai' validated?", "criteria": {"pattern: ^\\S+\\.tbi$": null, "type: boolean": null, "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "pattern: ^\\S+\\.crai$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 2}
{"id": "mod_oarfish_alignmentprojectionmode_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: oarfish is a program for quantifying transcript-level expression from long-read sequencing technologies. Project an existing spliced genome BAM (e.g. from minimap2 -ax splice) onto the annotated transcripts, then quantify. (tools: oarfish)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amrfinderplus/run": "Identify antimicrobial resistance in gene or protein sequences", "art/illumina": "Simulation tool to generate synthetic Illumina next-generation sequencing reads", "bamtofastq10x": "Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ATAC, Cell Ranger DNA, and Lon", "oarfish/alignmentprojectionmode": "oarfish is a program for quantifying transcript-level expression from long-read sequencing technologies. Proje", "kled": "An ultra-fast and sensitive structural variant detection tool for long-read sequencing data."}}, "target": "oarfish/alignmentprojectionmode", "target_idx": 3}
{"id": "mod_ngsbits_samplegender_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Determines the gender of a sample from the BAM/CRAM file. (tools: ngsbits)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bwameme/mem": null, "malt/run": null, "snapaligner/index": null, "bamreadcount": null, "ngsbits/samplegender": null}}, "target": "ngsbits/samplegender", "target_idx": 4}
{"id": "mod_samtools_collate_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: shuffles and groups reads together by their names (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ascat": "copy number profiles of tumour cells.", "gubbins": "Gubbins (Genealogies Unbiased By recomBinations In Nucleotide Sequences) is an algorithm that iteratively iden", "samtools/collate": "shuffles and groups reads together by their names", "find/unpigz": "A module for decompressing a large number of gzipped files, getting around the UNIX terminal argument limit", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files."}}, "target": "samtools/collate", "target_idx": 2}
{"id": "samplesheet_arch_pacbio_hifi_wgs_4_3", "category": "samplesheet_schema", "state": {"assay": "Long-read Pacific Biosciences HiFi sequencing", "first_step": "HIFIADAPTERFILT", "template": "nf-core/genomeassembler"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Single HiFi BAM or FastQ?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null, "sample,vcf": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "mod_cnvkit_export_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert copy number ratio tables (.cnr files) or segments (.cns) to another format. (tools: cnvkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cnvkit/batch": "Copy number variant detection from high-throughput sequencing data", "pirate": "Pangenome toolbox for bacterial genomes", "cnvkit/export": "Convert copy number ratio tables (.cnr files) or segments (.cns) to another format.", "cnvkit/genemetrics": "Copy number variant detection from high-throughput sequencing data", "proovframe/fix": "frame-shift correction for long read (meta)genomics - fix frameshifts in reads"}}, "target": "cnvkit/export", "target_idx": 2}
{"id": "mod_quast_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Quality Assessment Tool for Genome Assemblies (tools: quast)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"dotseq_dotseq": "Detect differential ORF usage (DOU) and ORF-level differential\ntranslation efficiency (DTE) from Ribo-seq with", "abricate_run": "Screen assemblies for antimicrobial resistance against multiple databases", "pypgx_preparedepthofcoverage": "Prepare a depth of coverage file for all target genes with SV from BAM files.", "abricate_summary": "Screen assemblies for antimicrobial resistance against multiple databases", "quast": "Quality Assessment Tool for Genome Assemblies"}}, "target": "quast", "target_idx": 4}
{"id": "samplesheet_arch_cancer_longitudinal_4_4", "category": "samplesheet_schema", "state": {"technology": "Cancer Genomics", "workflow_entry": "FASTQC", "library_inputs": "Serial plasma cfDNA and biopsy FASTQs across treatment intervals"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Serial plasma cfDNA and biopsy FASTQs across treatment intervals?", "criteria": {"sample,timepoint,fastq": null, "sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,sample,timepoint,status,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,status,fastq_1,fastq_2", "target_idx": 3}
{"id": "schema_std_detaxizer_1_0", "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": {"sample,id,data_path,fastq_dir,cytaimage": null, "sample,short_reads_fastq_1,short_reads_fastq_2,long_reads_fastq_1": null, "sample,fastq_1,fastq_2,barcode": null, "sample,fasta": null}}, "target": "sample,short_reads_fastq_1,short_reads_fastq_2,long_reads_fastq_1", "target_idx": 1}
{"id": "qc_adapt_pe_illumina_fastqc_2_41", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Standard Paired-end Illumina RNA-seq (short_reads_150bp).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "samplesheet_arch_rare_disease_trio_4_1", "category": "samplesheet_schema", "state": {"assay": "Trio exome/genome sequencing (Proband, Mother, Father)", "first_step": "FASTQC", "inputs": "Paired-end FASTQs with pedigree relationships and affected status"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end FASTQs with pedigree relationships and affected status?", "criteria": {"sample,bam,bai": null, "family_id,sample,fastq_1,fastq_2": null, "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_narfmap_align_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs fastq alignment to a reference using NARFMAP (tools: narfmap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"alignoth": "Creating alignment plots from bam files", "narfmap_align": "Performs fastq alignment to a reference using NARFMAP", "iphop_predict": "Predict phage host using iPHoP", "nextgenmap": "Performs fastq alignment to a fasta reference using NextGenMap", "abra2": "Assembly Based ReAligner for next-generation sequencing data"}}, "target": "narfmap_align", "target_idx": 1}
{"id": "resource_bases2fastq_5", "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_medium": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_centrifuge_centrifuge_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Classifies metagenomic sequence data (tools: centrifuge)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hmmer/eslsfetchindex": "Builds an SSI (sequence/subsequence index) file for a sequence file,\nusing the esl-sfetch utility, an Easel mi", "ganon/classify": "Classify FASTQ files against ganon database", "vt/normalize": "normalizes variants in a VCF file", "centrifuge/centrifuge": "Classifies metagenomic sequence data", "haplogrep3/classify": "classification into haplogroups"}}, "target": "centrifuge/centrifuge", "target_idx": 3}
{"id": "samplesheet_arch_dual_rnaseq_host_pathogen_0_0", "category": "samplesheet_schema", "state": {"assay": "Dual RNA-seq simultaneous host and pathogen transcriptomics", "first_step": "FASTQC", "inputs": "Paired-end FASTQs from infected tissue undergoing dual mapping to human and pathogen", "pipeline": "nf-core/dualrnaseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Dual RNA-seq simultaneous host and pathogen transcriptomics?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1,fastq_2,host,pathogen": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,host,pathogen", "target_idx": 2}
{"id": "mod_gcta_makegrm_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compute a whole dense GRM with GCTA (tools: gcta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gcta_adjustgrm": "Adjust a dense GRM for incomplete tagging using `gcta --grm-adj`", "gcta_bivariateremlldms": "Run bivariate REML-LDMS analysis with an MGRM manifest", "gcta_makegrm": "Compute a whole dense GRM with GCTA", "ilastik_pixelclassification": "Ilastik is a tool that utilizes machine learning algorithms to classify pixels, segment, track and count cells", "ensemblvep_vep": "Ensembl Variant Effect Predictor (VEP). The output-file-format is controlled through `task.ext.args`."}}, "target": "gcta_makegrm", "target_idx": 2}
{"id": "mod_elprep_fastatoelfasta_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert a file in FASTA format to the ELFASTA format (tools: elprep)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gstama/polyacleanup": "Helper script, remove remaining polyA sequences from Full Length Non Chimeric reads (Pacbio isoseq3)", "agrvate": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants", "elprep/fastatoelfasta": "Convert a file in FASTA format to the ELFASTA format", "any2fasta": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input ", "sentieon/bwaindex": "Create BWA index for reference genome"}}, "target": "elprep/fastatoelfasta", "target_idx": 2}
{"id": "noul_deprecated_file_output_syntax_20", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Declaring `output: file('*.bam')` is the modern DSL2 syntax rather than `path('*.bam')`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "core_tool_kallisto_bustools_described_0", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Ultra-fast pseudoalignment and barcode/UMI processing for single-cell RNA-seq generating bustools count matrices.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"alevin": "Salmon single-cell", "kallisto_bustools": "Kallisto bustools workflow for rapid single-cell RNA-seq quantification and UMI counting", "cellranger": "10x Chromium pipeline", "starsolo": "STAR single-cell", "salmon": "Bulk quantifier"}}, "target": "kallisto_bustools", "target_idx": 1}
{"id": "mod_picard_markduplicates_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Locate and tag duplicate reads in a BAM file (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biobambam/bammarkduplicates2": "Locate and tag duplicate reads in a BAM file", "fastq_fetch_clean_hostile": "Downloads required reference genomes for hostile and removes host reads from short-read FASTQ sequencing files", "picard/markduplicates": "Locate and tag duplicate reads in a BAM file", "amulety/embed": "A module to create embeddings of B-cell receptor (BCR) or T-cell receptor (TCR) amino acid sequences using amu", "gatk4spark/markduplicates": "This tool locates and tags duplicate reads in a BAM or SAM file, where duplicate reads are defined as originat"}}, "target": "picard/markduplicates", "target_idx": 2}
{"id": "resource_biscuit_biscuitblaster_3", "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_medium": null, "process_low": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_biobambam_bammarkduplicates2_4", "category": "resource_profiling", "state": {"process": "BIOBAMBAM_BAMMARKDUPLICATES2", "tool": "biobambam/bammarkduplicates2", "description": "Locate and tag duplicate reads in a BAM file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIOBAMBAM_BAMMARKDUPLICATES2 (Locate and tag duplicate reads in a BAM file) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_cancer_somatic_tn_0_0", "category": "samplesheet_schema", "state": {"assay": "Somatic cancer variant calling with tumor-normal pairs", "first_step": "BWA_MEM", "inputs": "Paired-end FASTQs for patient tumor and germline normal tissue", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Somatic cancer variant calling with tumor-normal pairs?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 3}
{"id": "local_subworkflow_irma_0_5", "category": "subworkflow_packaging", "state": {"subworkflow": "IRMA", "modules": ["irma"], "description": "Iterative assembly step for influenza and coronavirus"}, "question": {"type": "choice", "instructions": "How should IRMA (irma) be built?", "criteria": {"Local subworkflow IRMA": null, "Leave them out": null, "Use nf-core subworkflow irma": null, "Keep the modules in the main workflow": null}}, "target": "Local subworkflow IRMA", "target_idx": 0}
{"id": "resource_assemblyscan_0", "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_high": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "intent_debug_error_18", "category": "intent_routing", "state": "Classify this user request: \"ERROR ~ Error executing process > 'SAMTOOLS_SORT' (command not found, exit status 127)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes"}}, "target": "debug_error", "target_idx": 2}
{"id": "mod_yara_mapper_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Align reads to a reference genome using YARA (tools: yara)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vcf2zarr/convert": "Convert VCF data to the VCF Zarr specification reliably, in parallel or distributed over a cluster", "bbmap/align": "Align short or PacBio reads to a reference genome using BBMap", "manta/tumoronly": "Manta calls structural variants (SVs) and indels from mapped paired-end sequencing reads. It is optimized for ", "yara/mapper": "Align reads to a reference genome using YARA", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files."}}, "target": "yara/mapper", "target_idx": 3}
{"id": "mod_last_train_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Find suitable score parameters for sequence alignment (tools: last)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"nonpareil/nonpareil": null, "last/lastdb": null, "last/dotplot": null, "megan/daa2info": null, "last/train": null}}, "target": "last/train", "target_idx": 4}
{"id": "samplesheet_arch_dual_rnaseq_host_pathogen_2_0", "category": "samplesheet_schema", "state": {"technology": "Specialized RNA-seq", "workflow_entry": "FASTQC", "library_inputs": "Paired-end FASTQs from infected tissue undergoing dual mapping to human and pathogen"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2,host,pathogen": null, "sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,host,pathogen", "target_idx": 0}
{"id": "qc_adapt_ont_ultra_long_1_15", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "samplesheet_arch_cutandrun_pe_1_2", "category": "samplesheet_schema", "state": {"assay": "CUT&RUN / CUT&TAG chromatin profiling with IgG control", "first_step": "FASTQC", "inputs": "Paired-end low-input fragment FASTQs with target antibody and IgG negative control", "pipeline": "nf-core/cutandrun"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for CUT&RUN / CUT&TAG chromatin profiling with IgG control?", "criteria": {"sample,target,control": null, "sample,fastq_1,fastq_2,target,control": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_2_11", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "noul_mix_operator_async_emission_19", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.mix()` channel operator waits until all source channels have completed before emitting any items.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "qc_adapt_ffpe_wes_2_49", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "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_tiddit_sv_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Identify chromosomal rearrangements. (tools: sv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tiddit/sv": "Identify chromosomal rearrangements.", "famsa/guidetree": "Renders a guidetree in famsa", "msisensorpro/scan": "MSIsensor-pro evaluates Microsatellite Instability (MSI) for cancer patients with next generation sequencing d", "pbsv/discover": "pbsv - PacBio structural variant (SV) signature discovery tool", "rtgtools/svdecompose": "The svdecompose tool of RTG tools. It is used to decompose structural variants to BNDs"}}, "target": "tiddit/sv", "target_idx": 0}
{"id": "mod_blobtk_create_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Creates a minimal blobdir. (tools: btk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"blobtk_plot": "Creates differing styles of blobplots depending on provided arguments.", "vembrane_table": "Creates tabular (TSV) files from VCF/BCF data with flexible Python expressions", "pydamage_analyze": "Damage parameter estimation for ancient DNA", "blobtk_create": "Creates a minimal blobdir.", "bftools_showinf": "Extract OME xml data from OME-tif"}}, "target": "blobtk_create", "target_idx": 3}
{"id": "subworkflow_pkg_quant_tximport_summarizedexperiment_2", "category": "subworkflow_packaging", "state": {"subworkflow": "QUANT_TXIMPORT_SUMMARIZEDEXPERIMENT", "modules": ["custom/tx2gene", "tximeta/tximport", "summarizedexperiment/summarizedexperiment"], "description": "Post-process transcript-level quantification results using tximport to produce count matrices and SummarizedExperiment objects"}, "question": {"type": "choice", "instructions": "How should QUANT_TXIMPORT_SUMMARIZEDEXPERIMENT (custom/tx2gene, tximeta/tximport, summarizedexperiment/summarizedexperiment) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow QUANT_TXIMPORT_SUMMARIZEDEXPERIMENT": null, "Use nf-core subworkflow quant_tximport_summarizedexperiment": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow quant_tximport_summarizedexperiment", "target_idx": 2}
{"id": "mod_gatk4_gatherpileupsummaries_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: write your description here (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sentieon/staralign": "Align reads to a reference genome using Sentieon STAR", "gatk4/applyvqsr": "Apply a score cutoff to filter variants based on a recalibration table.\nAplyVQSR performs the second pass in a", "gatk4/gatherpileupsummaries": "write your description here", "bwafastalign/index": "Create BWA-FASTALIGN index for reference genome", "gatk4/applybqsr": "Apply base quality score recalibration (BQSR) to a bam file"}}, "target": "gatk4/gatherpileupsummaries", "target_idx": 2}
{"id": "noul_named_process_output_emits_24", "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": "schema_std_radseq_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/radseq", "assay": "radseq pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/radseq (Variant-calling pipeline for Restriction site-associated DNA)?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "fastq_1,fastq_2,group,replicate,md5_1": null, "sample,fastq_1,fastq_2,bam,bai": null, "sample,fastq_1,fastq_2,umi_barcodes": null}}, "target": "sample,fastq_1,fastq_2,umi_barcodes", "target_idx": 3}
{"id": "schema_std_longraredisease_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/longraredisease", "description": "Long read sequencing pipeline to identify variants in patients with neurodevelopmental disorders ", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/longraredisease?", "criteria": {"sample,trait,pascal,twas,additional_sources": null, "sample,seq_data,pbi,start_from": null, "sample,fastq_1,fastq_2,replicate,antibody": null, "family_id,sample,file_path,hpo_terms,sex": null}}, "target": "family_id,sample,file_path,hpo_terms,sex", "target_idx": 3}
{"id": "mod_freebayes_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A haplotype-based variant detector (tools: freebayes)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"freebayes": "A haplotype-based variant detector", "multivcfanalyzer": "SNP table generator from GATK UnifiedGenotyper with functionality geared for aDNA", "eigenstratdatabasetools/eigenstratsnpcoverage": "Provide the SNP coverage of each individual in an eigenstrat formatted dataset.", "biomformat/convert": "Convert biom table to different format.\nConversion between text tab-delimited, BIOM-v1 (JSON), and BIOM-v2 (HD", "motus/merge": "Taxonomic meta-omics profiling using universal marker genes"}}, "target": "freebayes", "target_idx": 0}
{"id": "mod_bbmap_bbsplit_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Split sequencing reads by mapping them to multiple references simultaneously (tools: bbmap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"manta/germline": "Manta calls structural variants (SVs) and indels from mapped paired-end sequencing reads. It is optimized for ", "bbmap/bbsplit": "Split sequencing reads by mapping them to multiple references simultaneously", "ampcombi2/complete": "A submodule that merges all output summary tables from ampcombi/parsetables in one summary file.", "ampcombi": "A tool to parse and summarise results from antimicrobial peptides tools and present functional classification.", "toulligqc": "A post sequencing QC tool for Oxford Nanopore sequencers"}}, "target": "bbmap/bbsplit", "target_idx": 1}
{"id": "qc_adapt_targeted_amplicon_2_10", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_openms_idscoreswitcher_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Switches between different scores of peptide or protein hits in identification data (tools: openms)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"shapeit5_switch": "Program to compute switch error rate and genotyping error rate given simulated or trio data.", "ngscheckmate_vafncm": "Determining whether sequencing data comes from the same individual by using SNP matching. This module generate", "tmb_pytmb": "This module calculates Tumor Mutational Burden (TMB) scores from VCF files using the pyTMB tool.", "pcangsd_inbreeding": "Estimate per-sample inbreeding coefficients from genotype likelihoods", "openms_idscoreswitcher": "Switches between different scores of peptide or protein hits in identification data"}}, "target": "openms_idscoreswitcher", "target_idx": 4}
{"id": "samplesheet_arch_rare_disease_trio_3_4", "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": "Define the required samplesheet CSV header schema for Trio exome/genome sequencing (Proband, Mother, Father) with entry step FASTQC.", "criteria": {"family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2": null}}, "target": "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2", "target_idx": 0}
{"id": "noul_multiple_script_sections_invalid_20", "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": "pipe_all101_molkart_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for fish analysis? Specific context: 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": {"molkart": "A pipeline for processing Molecular Cartography data from Resolve Bioscience (combinatorial FISH) [fish, image-processin", "coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]", "rnasplice": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis [alternative-splicing, rna, rna-seq]", "airrflow": "B-cell and T-cell Adaptive Immune Receptor Repertoire (AIRR) sequencing analysis pipeline using the Immcantation framewo", "metapep": "From metagenomes to epitopes and beyond"}}, "target": "molkart", "target_idx": 0}
{"id": "resource_blast_blastp_0", "category": "resource_profiling", "state": {"process": "BLAST_BLASTP", "tool": "blast/blastp", "description": "BLASTP (Basic Local Alignment Search Tool- Protein) compares an amino acid (protein) query sequence against a protein database"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLAST_BLASTP (BLASTP (Basic Local Alignment Search Tool- Protein) compares an amino acid (prot) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_ampliseq_its_fungal_3_0", "category": "samplesheet_schema", "state": {"assay": "Fungal ITS1/ITS2 marker gene amplicon surveillance", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Fungal ITS1/ITS2 marker gene amplicon surveillance with entry step FASTQC.", "criteria": {"sample,bam": null, "sample,unite_fasta": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "resource_biohansel_4", "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_low": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_subread_featurecounts_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Count reads that map to genomic features (tools: featurecounts)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/determinegermlinecontigploidy": "Determines the baseline contig ploidy for germline samples given counts data", "samtools/idxstats": "Reports alignment summary statistics for a BAM/CRAM/SAM file", "nanofilt": "Filtering and trimming of Oxford Nanopore Sequencing data", "samtools/sormadup": "Collate/Fixmate/Sort/Markdup SAM/BAM/CRAM file", "subread/featurecounts": "Count reads that map to genomic features"}}, "target": "subread/featurecounts", "target_idx": 4}
{"id": "qc_adapt_qc_aggregate_1_21", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Swap for NanoPlot": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_sourmash_index_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create a database of sourmash signatures (a group of FracMinHash sketches) to be used as references. (tools: sourmash)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"upd": null, "sourmash_index": null, "sequenzautils_gcwiggle": null, "sourmash_sketch": null, "sourmash_gather": null}}, "target": "sourmash_index", "target_idx": 1}
{"id": "mod_ucsc_bedgraphtobigwig_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert a bedGraph file to bigWig format. (tools: ucsc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bismark/methylationextractor": null, "ucsc/bedgraphtobigwig": null, "cnvkit/coverage": null, "lofreq/somatic": null, "ltrretriever/lai": null}}, "target": "ucsc/bedgraphtobigwig", "target_idx": 1}
{"id": "qc_adapt_pacbio_hifi_1_45", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "noul_include_modular_process_syntax_11", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `include { FASTQC } from './modules/fastqc/main'` is the correct syntax for importing a modular process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_rasusa_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Randomly subsample sequencing reads to a specified coverage (tools: rasusa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rasusa": null, "bbmap_bbnorm": null, "khmer_trimlowabund": null, "allelecounter": null, "umitools_extract": null}}, "target": "rasusa", "target_idx": 0}
{"id": "qc_adapt_qc_aggregate_2_7", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample QC aggregation and reporting (multiqc_report).", "criteria": {"Drop MultiQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "field_constraint_sex_3_8", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "sex", "validation_type": "pedigree_sex_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'sex'.", "criteria": {"enum: [1, 2, other, unknown] (1=male, 2=female)": null, "type: boolean": null, "pattern: ^\\S+\\.gz$": null, "format: file-path": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 0}
{"id": "resource_bcftools_plugintag2tag_5", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINTAG2TAG", "tool": "bcftools/plugintag2tag", "description": "Converts between similar tags, such as GL,PL,GP or QR,QA,QS or localized alleles, eg LPL,LAD."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINTAG2TAG (Converts between similar tags, such as GL,PL,GP or QR,QA,QS or localized alleles) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_gfaffix_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Collapse walk-preserving shared affixes in variation graphs in GFA format (tools: gfaffix)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"dshbio_exportsegments": "Export assembly segment sequences in GFA 1.0 format to FASTA format", "amulety_antiberty": "A module to create antiberty embeddings of antibody (BCR) amino acid sequences using amulety.", "islandpath": "Genomic island prediction in bacterial and archaeal genomes", "gfatools_stat": "Summary statistics for GFA files", "gfaffix": "Collapse walk-preserving shared affixes in variation graphs in GFA format"}}, "target": "gfaffix", "target_idx": 4}
{"id": "schema_std_phaseimpute_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/phaseimpute. Description: A bioinformatics pipeline to phase and impute genetic data.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/phaseimpute.", "criteria": {"fastq_1,fastq_2,group,replicate,control": null, "gene_name,alignment,tree,suite,tool": null, "sample,tools,file,index": null, "sample,bam,bai,cram,crai": null}}, "target": "sample,tools,file,index", "target_idx": 2}
{"id": "schema_std_provenancereport_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/provenancereport", "description": "A simple provenance reporting pipeline", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/provenancereport?", "criteria": {"family_id,sample,file_path,hpo_terms,sex": null, "id,path": null, "gene_name,alignment,tree,suite,tool": null, "condition,type,microbiome_path,alleles,weights_path": null}}, "target": "id,path", "target_idx": 1}
{"id": "samplesheet_arch_ont_metagenome_single_3_0", "category": "samplesheet_schema", "state": {"assay": "Long-read Oxford Nanopore environmental metagenomic sequencing", "first_step": "NANOPLOT"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Long-read Oxford Nanopore environmental metagenomic sequencing with entry step NANOPLOT.", "criteria": {"sample,fastq_1,group": null, "sample,bam": null, "sample,fastq_1,fastq_2,group": null, "sample,fasta": null}}, "target": "sample,fastq_1,group", "target_idx": 0}
{"id": "mod_picrust2_pipeline_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Predict metagenome functional content from marker gene sequences and OTU/ASV abundance data (tools: picrust2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"binette": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning", "picrust2/pipeline": "Predict metagenome functional content from marker gene sequences and OTU/ASV abundance data", "fastq_align_mapad": "Align FASTQ files against reference genome with the mapAD aDNA short-read aligner producing a sorted and index", "tcoffee/seqreformat": "Reformats files with t-coffee", "bracken/combinebrackenoutputs": "Combine output of metagenomic samples analyzed by bracken."}}, "target": "picrust2/pipeline", "target_idx": 1}
{"id": "mod_bcl2fastq_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Demultiplex Illumina BCL files (tools: bcl2fastq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"holodeck_mutate": "Generate a VCF of random mutations from a reference genome with holodeck", "bcl2fastq": "Demultiplex Illumina BCL files", "mgikit_demultiplex": "Demultiplex MGI fastq files", "epang_place": "phylogenetic placement of query sequences in a reference tree", "qcat": "Demultiplexer for Nanopore samples"}}, "target": "bcl2fastq", "target_idx": 1}
{"id": "samplesheet_arch_pacbio_hifi_wgs_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/genomeassembler", "assay_type": "Long-read Pacific Biosciences HiFi sequencing", "data_format": "Single HiFi BAM or FastQ"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "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": "samplesheet_arch_vcf_annotation_pipeline_1_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": "Which columns should the samplesheet have for Downstream functional annotation of pre-called VCF files?", "criteria": {"sample,vcf,tbi": null, "sample,bed": null, "sample,fastq_1,fastq_2": null, "sample,bam,bai": null}}, "target": "sample,vcf,tbi", "target_idx": 0}
{"id": "resource_bedtools_nuc_5", "category": "resource_profiling", "state": {"process": "BEDTOOLS_NUC", "tool": "bedtools/nuc", "description": "Profiles the nucleotide content of intervals in a fasta file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_NUC (Profiles the nucleotide content of intervals in a fasta file.) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "schema_std_genomicrelatedness_2_0", "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,fastq_1,fastq_2,bam,cram": null, "sample,input,output_path,checksum_md5,checksum_sha": null, "sample,trait,pascal,twas,additional_sources": null, "sample,fasta,protein,gbk,gff": null}}, "target": "sample,fastq_1,fastq_2,bam,cram", "target_idx": 0}
{"id": "mod_deepvariant_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": {"bcftools/consensus": "Compresses VCF files", "pairtools/restrict": "Assign restriction fragments to pairs", "deepvariant": "DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generat", "atlas/call": "generate VCF file from a BAM file using various calling methods", "bam_dedup_stats_samtools_umitools": "UMI-tools dedup, index BAM file and run samtools stats, flagstat and idxstats"}}, "target": "deepvariant", "target_idx": 2}
{"id": "mod_krona_ktimporttaxonomy_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: KronaTools Import Taxonomy imports taxonomy classifications and produces an interactive Krona plot. (tools: krona)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abundance_differential_filter": "A subworkflow for filtering differential abundance results", "deeptools_plotprofile": "plots values produced by deeptools_computematrix as a profile plot", "graphmap2_align": "A versatile pairwise aligner for genomic and spliced nucleotide sequences", "krona_ktimporttaxonomy": "KronaTools Import Taxonomy imports taxonomy classifications and produces an interactive Krona plot.", "deeptools_plotfingerprint": "plots cumulative reads coverages by BAM file"}}, "target": "krona_ktimporttaxonomy", "target_idx": 3}
{"id": "mod_angsd_realsfs_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Estimate site frequency spectrum from site allele frequencies (tools: angsd)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vizgenpostprocessing/runsegmentationontile": "The module runs the segmentation algorithm on a specific tile using Vizgen's\npost-processing tool.", "angsd/gl": "Calculated genotype likelihoods from BAM files.", "bam_docounts_contamination_angsd": "Calculate contamination of the X-chromosome with ANGSD", "angsd/realsfs": "Estimate site frequency spectrum from site allele frequencies", "jvarkit/vcfpolyx": "annotate VCF files for poly repeats"}}, "target": "angsd/realsfs", "target_idx": 3}
{"id": "resource_annotsv_installannotations_1", "category": "resource_profiling", "state": {"process": "ANNOTSV_INSTALLANNOTATIONS", "tool": "annotsv/installannotations", "description": "Install the AnnotSV annotations"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANNOTSV_INSTALLANNOTATIONS (Install the AnnotSV annotations) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_seqkit_seq_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Transforms sequences (extract ID, filter by length, remove gaps, reverse complement...) (tools: seqkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ascat": "copy number profiles of tumour cells.", "agat/spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "agat/spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "seqkit/seq": "Transforms sequences (extract ID, filter by length, remove gaps, reverse complement...)", "orfm": "A simple and not slow open reading frame (ORF) caller. The goal is to return a FASTA file of open reading fram"}}, "target": "seqkit/seq", "target_idx": 3}
{"id": "resource_agat_spkeeplongestisoform_2", "category": "resource_profiling", "state": {"process": "AGAT_SPKEEPLONGESTISOFORM", "tool": "agat/spkeeplongestisoform", "description": "Filters GFF records to keep only the longest isoform per gene"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SPKEEPLONGESTISOFORM (Filters GFF records to keep only the longest isoform per gene) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_cageseq_transcription_0_4", "category": "samplesheet_schema", "state": {"technology": "Specialized RNA-seq", "workflow_entry": "FASTQC", "library_inputs": "Single-end capped 5-prime cDNA tags for transcription start site (TSS) mapping"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: CAGE-seq 5-prime capped transcript end sequencing?", "criteria": {"sample,tss_bed": null, "sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "intent_build_pipeline_19", "category": "intent_routing", "state": "Classify this user request: \"Can you generate a Nextflow DSL2 pipeline for paired-end Illumina RNA-seq with FastQC, STAR, and featureCounts?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": null, "prepare_data": null, "build_pipeline": null, "debug_error": null}}, "target": "build_pipeline", "target_idx": 2}
{"id": "resource_bwa_mem_0", "category": "resource_profiling", "state": {"process": "BWA_MEM", "tool": "bwa/mem", "description": "Performs fastq alignment to a fasta reference using BWA"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWA_MEM (Performs fastq alignment to a fasta reference using BWA) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_high": null, "process_single": null}}, "target": "process_high", "target_idx": 2}
{"id": "resource_ampcombi2_cluster_0", "category": "resource_profiling", "state": {"process": "AMPCOMBI2_CLUSTER", "tool": "ampcombi2/cluster", "description": "A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete using MMseqs2 cluster."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMPCOMBI2_CLUSTER (A submodule that clusters the merged AMP hits generated from ampcombi2/parsetabl) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "resource_agat_spstatistics_2", "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_single": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_cfdna_liquid_biopsy_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/oncoanalyser", "assay_type": "Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking", "data_format": "Circulating tumor DNA FASTQs across patient clinical draw intervals"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"patient,sample,timepoint,volume_ml,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,timepoint,fastq": null}}, "target": "patient,sample,timepoint,volume_ml,fastq_1,fastq_2", "target_idx": 0}
{"id": "schema_std_chipseq_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/chipseq", "description": "ChIP-seq peak-calling, QC and differential analysis pipeline.", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/chipseq?", "criteria": {"sample,group,path,ref,method": null, "seeds,network,perturbed_networks": null, "sample,alleles,mhc_class,filename": null, "sample,fastq_1,fastq_2,replicate,antibody": null}}, "target": "sample,fastq_1,fastq_2,replicate,antibody", "target_idx": 3}
{"id": "resource_bcftools_reheader_0", "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_long": null, "process_low": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_bcftools_pluginimputeinfo_0", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINIMPUTEINFO", "tool": "bcftools/pluginimputeinfo", "description": "Adds imputation information metrics to the INFO field based on selected FORMAT tags. Only the IMPUTE2 INFO metric from FORMAT/GP tags is currently available."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINIMPUTEINFO (Adds imputation information metrics to the INFO field based on selected FORMAT t) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_metagenome_mag_grouped_7_1", "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 grouped metagenomics?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fasta": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 3}
{"id": "resource_bff_3", "category": "resource_profiling", "state": {"process": "BFF", "tool": "bff", "description": "Generating cell hashing calls from a matrix of count data."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BFF (Generating cell hashing calls from a matrix of count data.) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "noul_publishdir_directive_usage_20", "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": "pipe_all101_chipseq_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for chip analysis? Specific context: 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": {"hlatyping": "Precision HLA typing from next-generation sequencing data [dna, hla, hla-typing]", "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", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline [atac-seq, chromatin-accessibiity]", "smrnaseq": "A small-RNA sequencing analysis pipeline [small-rna, smrna-seq]", "cutandrun": "Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak callin", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 [16s, 18s, amplicon-sequencing]", "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]", "chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. [chip, chip-seq, chromatin-immunoprecipitation]"}}, "target": "chipseq", "target_idx": 9}
{"id": "resource_bamtofastq10x_3", "category": "resource_profiling", "state": {"process": "BAMTOFASTQ10X", "tool": "bamtofastq10x", "description": "Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ATAC, Cell Ranger DNA, and Long Ranger back to FASTQ files that can be used as inputs to re-run analysis"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMTOFASTQ10X (Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_proteomics_dia_1_5", "category": "samplesheet_schema", "state": {"assay": "Data-Independent Acquisition (DIA) quantitative mass spectrometry", "first_step": "INPUT_CHECK", "template": "nf-core/diaproteomics"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Data-Independent Acquisition (DIA) quantitative mass spectrometry?", "criteria": {"sample,fasta": null, "sample,peptides_tsv": null, "sample,raw_file,condition": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,raw_file,condition", "target_idx": 2}
{"id": "pipe_all101_magmap_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Best-practice analysis pipeline for mapping reads to a (large) collections of genomes. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"demo": "nf-core/demo is a simple nf-core style bioinformatics pipeline for workshops and demos. [demo, minimal-example, training", "bacass": "Simple bacterial assembly and annotation pipeline [assembly, bacterial-genomes, denovo]", "pangenome": "Renders a collection of sequences into a pangenome graph. https://doi.org/10.1093/bioinformatics/btae609. [pangenome]", "stableexpression": "This pipeline is designed to identify the most stable genes in one or more expression datasets (RNA-seq / Microarray). T", "magmap": "Best-practice analysis pipeline for mapping reads to a (large) collections of genomes", "pairgenomealign": "Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plo", "seqinspector": "Dedicated QC-only pipeline for sequencing data. The pipeline will run a (potentially large) set of QC tools and can outp", "rnadnavar": "Pipeline for RNA and DNA integrated analysis for somatic mutation detection"}}, "target": "magmap", "target_idx": 4}
{"id": "samplesheet_arch_proteomics_dia_1_4", "category": "samplesheet_schema", "state": {"assay": "Data-Independent Acquisition (DIA) quantitative mass spectrometry", "first_step": "INPUT_CHECK"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Data-Independent Acquisition (DIA) quantitative mass spectrometry?", "criteria": {"sample,raw_file,condition": null, "sample,peptides_tsv": null, "sample,mzml": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,raw_file,condition", "target_idx": 0}
{"id": "mod_vsearch_sintax_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Taxonomic classification using the sintax algorithm. (tools: vsearch)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"smncopynumbercaller": "tool to call the copy number of full-length SMN1, full-length SMN2, as well as SMN2Δ7–8 (SMN2 with a deletion ", "bbmap_sendsketch": "Compares query sketches to reference sketches hosted on a remote server via the Internet.", "icountmini_metagene": "Plot a metagene of cross-link events/sites around various transcriptomic landmarks.", "vsearch_fastqfilter": "Performs quality filtering and / or conversion of a FASTQ file to FASTA format.", "vsearch_sintax": "Taxonomic classification using the sintax algorithm."}}, "target": "vsearch_sintax", "target_idx": 4}
{"id": "pipe_all101_epitopeprediction_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: 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": {"epitopeprediction": "A bioinformatics best-practice analysis pipeline for epitope prediction and annotation [epitope, epitope-prediction, mhc", "kmermaid": " k-mer similarity analysis pipeline [k-mer, kmer, kmer-counting]", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "bactmap": "A mapping-based pipeline for creating a phylogeny from bacterial whole genome sequences [bacteria, bacterial, bacterial-", "denovotranscript": "A pipeline for de novo transcriptome assembly of paired-end short reads from bulk RNA-seq [denovo-assembly, rna-seq, tra", "fastqrepair": "A pipeline that can be used to recover corrupted FASTQ.gz files, drop or fix uncompliant reads, remove unpaired reads, a", "reportho": "nf-core pipeline for comparative analysis of ortholog predictions [ortholog]", "drop": "Pipeline to find aberrant events in RNA-Seq data, useful for diagnosis of rare disorders", "raredisease": "Call and score variants from WGS/WES of rare disease patients. [diagnostics, rare-disease, snv]", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline [atac-seq, chromatin-accessibiity]"}}, "target": "epitopeprediction", "target_idx": 0}
{"id": "qc_adapt_bulk_multiqc_0_40", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For High-throughput bulk WGS multi-sample run, what is the recommended QC default for MultiQC?", "criteria": {"Swap for NanoPlot": null, "Drop MultiQC": null, "Keep MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_clusty_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Clusty is a tool for large-scale clustering using sparse distance matrices, suitable for datasets with millions of objects. (tools: clusty)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"clusty": "Clusty is a tool for large-scale clustering using sparse distance matrices, suitable for datasets with million", "haplogrep3/classify": "classification into haplogroups", "cdhit/cdhit": "Cluster protein sequences using sequence similarity", "galah": "Cluster genome FASTA files by average nucleotide identity", "foldmason/createdb": "Creates a database for Foldmason."}}, "target": "clusty", "target_idx": 0}
{"id": "samplesheet_arch_bulk_wgs_pe_6_4", "category": "samplesheet_schema", "state": {"assay": "Standard Paired-end Whole Genome Sequencing (WGS)", "first_step": "FASTQC", "inputs": "Raw paired-end Illumina WGS FASTQs", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns are standard for Standard Paired-end Whole Genome Sequencing (WGS) input samplesheet?", "criteria": {"sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "field_constraint_sample_1_5", "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, "pattern: ^\\S+$ (no whitespace, unique)": null, "enum: [0, 1]": null, "format: file-path": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 1}
{"id": "mod_mygene_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Fetch the GO concepts for a list of genes (tools: mygene)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mygene": null, "annotsv_annotsv": null, "agat_spflagshortintrons": null, "custom_orfnormalise": null, "bbmap_align": null}}, "target": "mygene", "target_idx": 0}
{"id": "noul_channel_factory_inside_process_body_18", "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": "samplesheet_arch_pediatric_trio_somatic_4_2", "category": "samplesheet_schema", "state": {"assay": "Pediatric cancer trio (Child Proband tumor, Proband germline, Parents)", "first_step": "FASTQC"}, "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,bam,bai": null, "family_id,sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "family_id,patient,sample,status,sex,fastq_1,fastq_2": null}}, "target": "family_id,patient,sample,status,sex,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_vamb_bin_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Variational autoencoder for metagenomic binning (tools: vamb)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vamb/bin": "Variational autoencoder for metagenomic binning", "custom/clustermetrics": "Computes clustering quality metrics (silhouette, Calinski-Harabasz, Davies-Bouldin) and performs k-sweep analy", "custom/clustervisualization": "Generates UMAP and t-SNE visualizations colored by cluster", "bam_rseqc": "Subworkflow to run multiple commands in the RSeqC package", "sentieon/varcal": "Module for Sentieons VarCal. The VarCal algorithm calculates the Variant Quality Score Recalibration (VQSR).\nV"}}, "target": "vamb/bin", "target_idx": 0}
{"id": "noul_channel_join_operator_14", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.join()` operator combines two channels sharing a matching key (like `meta.id`).\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_odgi_view_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Project a graph into other formats. (tools: odgi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"odgi/view": "Project a graph into other formats.", "fastq_remove_rrna": "Remove ribosomal RNA reads from FASTQ files using SortMeRNA, RiboDetector, or Bowtie2", "ribocode/metaplots": "Set up RiboCode ORF calling with metaplots", "odgi/build": "Construct a dynamic succinct variation graph in ODGI format from a GFAv1.", "gfaffix": "Collapse walk-preserving shared affixes in variation graphs in GFA format"}}, "target": "odgi/view", "target_idx": 0}
{"id": "subworkflow_pkg_vcf_annotate_snpeff_0", "category": "subworkflow_packaging", "state": {"subworkflow": "VCF_ANNOTATE_SNPEFF", "modules": ["snpeff", "snpeff/snpeff", "htslib/bgziptabix"], "description": "Perform annotation with snpEff and bgzip + tabix index the resulting VCF file"}, "question": {"type": "choice", "instructions": "How should VCF_ANNOTATE_SNPEFF (snpeff, snpeff/snpeff, htslib/bgziptabix) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow VCF_ANNOTATE_SNPEFF": null, "Leave them out": null, "Use nf-core subworkflow vcf_annotate_snpeff": null}}, "target": "Use nf-core subworkflow vcf_annotate_snpeff", "target_idx": 3}
{"id": "pipe_all101_ampliseq_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for 16s. 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]", "variantbenchmarking": "Pipeline to evaluate and validate the accuracy of variant calling methods in genomic research [benchmark, small-variants", "magmap": "Best-practice analysis pipeline for mapping reads to a (large) collections of genomes", "hic": "Analysis of Chromosome Conformation Capture data (Hi-C) [chromosome-conformation-capture, hi-c]", "metapep": "From metagenomes to epitopes and beyond", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 [16s, 18s, amplicon-sequencing]", "hlatyping": "Precision HLA typing from next-generation sequencing data [dna, hla, hla-typing]", "genomeassembler": "Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads [genome-assembly]"}}, "target": "ampliseq", "target_idx": 5}
{"id": "mod_oncocnv_0", "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": {"cnvkit/antitarget": null, "oncocnv": null, "gcta/bivariatereml": null, "dastool/dastool": null, "cnvkit/reference": null}}, "target": "oncocnv", "target_idx": 1}
{"id": "resource_autocycler_trim_4", "category": "resource_profiling", "state": {"process": "AUTOCYCLER_TRIM", "tool": "autocycler/trim", "description": "Trim cluster assembly graphs to remove unsupported segments prior to resolution."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AUTOCYCLER_TRIM (Trim cluster assembly graphs to remove unsupported segments prior to resolution.) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_0_41", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "qc_adapt_ont_ultra_long_2_1", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "resource_bismark_methylationextractor_0", "category": "resource_profiling", "state": {"process": "BISMARK_METHYLATIONEXTRACTOR", "tool": "bismark/methylationextractor", "description": "Extracts methylation information for individual cytosines from alignments."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_METHYLATIONEXTRACTOR (Extracts methylation information for individual cytosines from alignments.) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "local_subworkflow_daisribosome_2_4", "category": "subworkflow_packaging", "state": {"subworkflow": "DAISRIBOSOME", "modules": ["dais"], "description": "Custom ribosomal frameshift translation analysis"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for DAISRIBOSOME (dais).", "criteria": {"Use nf-core subworkflow daisribosome": null, "Keep the modules in the main workflow": null, "Local subworkflow DAISRIBOSOME": null, "Leave them out": null}}, "target": "Local subworkflow DAISRIBOSOME", "target_idx": 2}
{"id": "resource_bio2zarr_vcf2zarrexplode_1", "category": "resource_profiling", "state": {"process": "BIO2ZARR_VCF2ZARREXPLODE", "tool": "bio2zarr/vcf2zarrexplode", "description": "Convert VCF(s) to intermediate columnar format (ICF)"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIO2ZARR_VCF2ZARREXPLODE (Convert VCF(s) to intermediate columnar format (ICF)) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_blast_makeblastdb_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Builds a BLAST database (tools: blast)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"any2fasta": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input ", "medaka": "A tool to create consensus sequences and variant calls from nanopore sequencing data", "xeniumranger/resegment": "The xeniumranger resegment module allows you to generate a new segmentation of the morphology image space by r", "abritamr/run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes", "blast/makeblastdb": "Builds a BLAST database"}}, "target": "blast/makeblastdb", "target_idx": 4}
{"id": "subworkflow_pkg_fastq_contam_seqtk_kraken_2", "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, "Use nf-core subworkflow fastq_contam_seqtk_kraken": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Use nf-core subworkflow fastq_contam_seqtk_kraken", "target_idx": 1}
{"id": "mod_custom_catadditionalfasta_0", "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": {"fastq_align_bwaaln": null, "any2fasta": null, "custom/catadditionalfasta": null, "ataqv/ataqv": null, "abritamr/run": null}}, "target": "custom/catadditionalfasta", "target_idx": 2}
{"id": "mod_strdust_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Tandem repeat genotyper for long reads (tools: STRdust)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"savana_run": "Identify and cluster SV breakpoints from long-read alignments.", "trtools_mergestr": "MergeSTR merges multiple VCF files produced by the same TR genotyper into a single VCF file.", "gatk4_markduplicates": "This tool locates and tags duplicate reads in a BAM or SAM file, where duplicate reads are defined as originat", "strdust": "Tandem repeat genotyper for long reads", "hmmer_hmmemit": "emit sequences from a profile HMM"}}, "target": "strdust", "target_idx": 3}
{"id": "mod_bam_impute_quilt_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subworkflow to impute BAM files using QUILT software.\nVariants location to impute are obtain through the tsv file given.\n\"regionout\", \"regionoutPadded\", \"regionSize\" keys will be added to the meta map to distinguish\nthe different files before ligation and therefore should not be used. (tools: bam_impute_quilt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bam_impute_quilt": "Subworkflow to impute BAM files using QUILT software.\nVariants location to impute are obtain through the tsv f", "vcf_phase_shapeit5": "Subworkflow to phase a reference panel VCF file using SHAPEIT5.\nThe panel is first chunked by chromosome by gl", "atlas/pmd": "Estimate the post-mortem damage patterns of DNA", "ascat": "copy number profiles of tumour cells.", "bwa/samse": "Convert bwa SA coordinate file to SAM format"}}, "target": "bam_impute_quilt", "target_idx": 0}
{"id": "mod_any2fasta_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input files may be gzip, bzip2, zip, or zstd compressed. (tools: any2fasta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rpbp/estimateorfbayesfactors": "Score every candidate ORF for evidence of active translation. For\neach ORF, Rp-Bp fits two competing Bayesian ", "agrvate": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants", "arcane/filter": "Filter GTF annotations and genome sequence for alignment-free single-cell RNA-seq quantification with Arcane", "gatk4/mergevcfs": "Merges several vcf files", "any2fasta": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input "}}, "target": "any2fasta", "target_idx": 4}
{"id": "mod_ska_distance_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate pairwise distances and basic clustering from SKA sketches (tools: ska)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ska/distance": "Calculate pairwise distances and basic clustering from SKA sketches", "cadd": "CADD is a tool for scoring the deleteriousness of single nucleotide variants as well as insertion/deletions va", "alignoth": "Creating alignment plots from bam files", "agat/spfilterfeaturefromkilllist": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID", "hipstr": "Genotype and phase short tandem repeats using Illumina whole-genome sequencing data"}}, "target": "ska/distance", "target_idx": 0}
{"id": "pipe_all101_proteinannotator_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Generation of sequence-level annotations for amino acid sequences. Topics: annotation, proteomics. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"diaproteomics": "Automated quantitative analysis of DIA proteomics mass spectrometry measurements. [data-independent-proteomics, dia-prot", "viralmetagenome": "A nf-core pipeline for untargeted whole genome reconstruction with iSNV detection from metagenomic samples.  [epidemiolo", "metaboigniter": "Pre-processing of mass spectrometry-based metabolomics data with quantification and identification based on MS1 and MS2 ", "proteinannotator": "Generation of sequence-level annotations for amino acid sequences [annotation, proteomics]", "proteogenomicsdb": "The ProteoGenomics database generation workflow creates different protein databases for ProteoGenomics data analysis. [c", "phaseimpute": "A bioinformatics pipeline to phase and impute genetic data [genomics, genotype, imputation]", "bamtofastq": "Converts bam or cram files to fastq format and does quality control. [bamtofastq, conversion, cramtofastq]", "differentialabundance": "Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq  [atac-seq, chip-seq, d", "rnadnavar": "Pipeline for RNA and DNA integrated analysis for somatic mutation detection", "longraredisease": "Long read sequencing pipeline to identify variants in patients with neurodevelopmental disorders  [nanopore, pacbio]"}}, "target": "proteinannotator", "target_idx": 3}
{"id": "qc_adapt_singlecell_multiqc_0_24", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "qc_adapt_ffpe_wes_0_27", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "field_constraint_bam_1_9", "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, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "format: uri": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 1}
{"id": "mod_picard_collectmultiplemetrics_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Collect multiple metrics from a BAM file (tools: picard)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"picard/collectmultiplemetrics": null, "hmmer/eslreformat": null, "busco/phylogenomics": null, "gcta/keep": null, "ashlar": null}}, "target": "picard/collectmultiplemetrics", "target_idx": 0}
{"id": "subworkflow_pkg_fasta_newick_epang_gappa_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_NEWICK_EPANG_GAPPA", "modules": ["hmmer/hmmbuild", "hmmer/hmmalign", "hmmer/eslalimask", "hmmer/eslreformat", "clustalo/align", "mafft/align", "epang/place", "epang/split", "gappa/examinegraft", "gappa/examineassign", "gappa/examineheattree"], "description": "Run phylogenetic placement with a number of query sequences plus a reference alignment and phylogeny. Used in nf-core/phyloplace."}, "question": {"type": "choice", "instructions": "How should FASTA_NEWICK_EPANG_GAPPA (hmmer/hmmbuild, hmmer/hmmalign, hmmer/eslalimask, hmmer/eslreformat, clustalo/align, mafft/align, epang/place, epang/split, gappa/examinegraft, gappa/examineassign, gappa/examineheattree) be structured in DSL2?", "criteria": {"Local subworkflow FASTA_NEWICK_EPANG_GAPPA": null, "Use nf-core subworkflow fasta_newick_epang_gappa": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fasta_newick_epang_gappa", "target_idx": 1}
{"id": "samplesheet_arch_metatranscriptome_denovo_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/metatdenovo", "assay_type": "Environmental community metatranscriptomics de novo assembly", "data_format": "Paired-end total RNA reads from complex microbial communities with ribosomal RNA filtering"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,rrna_fasta": null, "sample,bam": null, "sample,fastq_1,fastq_2,environment": null}}, "target": "sample,fastq_1,fastq_2,environment", "target_idx": 3}
{"id": "noul_deprecated_file_output_syntax_16", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Declaring `output: file('*.bam')` is the modern DSL2 syntax rather than `path('*.bam')`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_germline_lane_split_5_3", "category": "samplesheet_schema", "state": {"assay": "Multi-lane Illumina sequencing run of clinical samples", "first_step": "FASTQC", "inputs": "FASTQ files split across flowcell lanes (L001, L002) needing RG alignment"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Multi-lane Illumina sequencing run of clinical samples.", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null, "patient,sample,lane,fastq_1,fastq_2": null, "lane,fastq_1,fastq_2": null}}, "target": "patient,sample,lane,fastq_1,fastq_2", "target_idx": 2}
{"id": "schema_std_funcscan_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/funcscan", "assay": "funcscan pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/funcscan ((Meta-)genome screening for functional and natural product g)?", "criteria": {"sample,condition,assay,peak_file,footprinting": null, "sample,fasta,protein,gbk,gff": null, "sample_id,name,description,path,path_2": null, "sample,fastq_1,fastq_2,strandedness,type": null}}, "target": "sample,fasta,protein,gbk,gff", "target_idx": 1}
{"id": "samplesheet_arch_ampliseq_its_fungal_6_0", "category": "samplesheet_schema", "state": {"technology": "Microbiome Amplicon", "workflow_entry": "FASTQC", "library_inputs": "Demultiplexed paired-end Illumina MiSeq ITS fungal amplicon reads"}, "question": {"type": "choice", "instructions": "Which columns are standard for Fungal ITS1/ITS2 marker gene amplicon surveillance input samplesheet?", "criteria": {"sample,primer_its1,primer_its2": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,unite_fasta": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "pipe_all101_fastquorum_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for consensus. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"seqsubmit": "nf-core pipeline for data submission to ENA", "kmermaid": " k-mer similarity analysis pipeline [k-mer, kmer, kmer-counting]", "fastquorum": "Pipeline to produce consensus reads using unique molecular indexes/barcodes (UMIs) [consensus, umi, umis]", "rnasplice": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis [alternative-splicing, rna, rna-seq]", "methylong": "Extract methylation calls from long reads (ONT/ PacBio)  [dna-methylation, fiber-seq, long-read]", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline [adna, ancient-dna-analysis, ancientdna]", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina", "drop": "Pipeline to find aberrant events in RNA-Seq data, useful for diagnosis of rare disorders", "pairgenomealign": "Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plo", "hlatyping": "Precision HLA typing from next-generation sequencing data [dna, hla, hla-typing]"}}, "target": "fastquorum", "target_idx": 2}
{"id": "mod_nacho_qc_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: NACHO (NAnostring quality Control dasHbOard) is developed for NanoString nCounter data.\nNanoString nCounter data is a messenger-RNA/micro-RNA (mRNA/miRNA) expression assay and works with fluorescent barcodes.\nEach barcode is assigned a mRNA/miRNA, which can be counted after bonding with its target.\nAs a result each count of a specific barcode represents the presence of its target mRNA/miRNA. (tools: NACHO)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ncbigenomedownload": null, "rseqc_tin": null, "nacho_normalize": null, "mirtop_counts": null, "nacho_qc": null}}, "target": "nacho_qc", "target_idx": 4}
{"id": "core_tool_minimap2_bare_2", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Long-read mapping of Oxford Nanopore and PacBio HiFi sequencing reads against human and microbial reference assemblies.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"subread": null, "star": null, "bowtie2": null, "bwa_mem": null, "minimap2": null}}, "target": "minimap2", "target_idx": 4}
{"id": "resource_bcftools_stats_2", "category": "resource_profiling", "state": {"process": "BCFTOOLS_STATS", "tool": "bcftools/stats", "description": "Generates stats from VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_STATS (Generates stats from VCF files) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_circularmapper_circulargenerator_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A method to improve mappings on circular genomes, using the BWA mapper. (tools: circulargenerator)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gangstr": null, "bwa/aln": null, "circularmapper/circulargenerator": null, "bwa/mem": null, "sequencetools/pileupcaller": null}}, "target": "circularmapper/circulargenerator", "target_idx": 2}
{"id": "field_constraint_phenotype_3_12", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "phenotype", "validation_type": "pedigree_phenotype_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'phenotype'.", "criteria": {"type: string free-text": null, "enum: [normal, tumor]": null, "format: file-path": null, "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 3}
{"id": "samplesheet_arch_bulk_rnaseq_se_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/rnaseq --input samplesheet.csv (Assay: Single-end Illumina RNA-seq with strandedness)", "question": {"type": "choice", "instructions": "Which columns are standard for Single-end Illumina RNA-seq with strandedness input samplesheet?", "criteria": {"sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,strandedness": null, "sample,vcf": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 1}
{"id": "intent_ask_question_7", "category": "intent_routing", "state": "Classify this user request: \"How does the .mix() operator differ from .combine() in Nextflow?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": null, "build_pipeline": null, "debug_error": null, "prepare_data": null}}, "target": "ask_question", "target_idx": 0}
{"id": "schema_std_scnanoseq_1_0", "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,bundle,image": null, "sample,fastq,cell_count": null, "sample,fastq_1,fastq_2,sampleID,forwardReads": null, "sample,fastq_1,fastq_2,bam,cram": null}}, "target": "sample,fastq,cell_count", "target_idx": 1}
{"id": "field_constraint_fastq_1_1_1", "category": "samplesheet_schema", "state": {"column": "fastq_1", "purpose": "Path to read 1 FASTQ file (gzipped or uncompressed)"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'fastq_1' (Path to read 1 FASTQ file (gzipped or uncompressed)).", "criteria": {"type: integer": null, "enum: [auto, forward, reverse, unstranded]": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 2}
{"id": "qc_adapt_ont_nanoplot_0_0", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_orftable_fasta_gtf_buildorfcatalogue_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Build a multi-caller Ribo-seq ORF catalogue from per-sample, per-caller\nORF prediction tables. Chains:\n\n  1. `custom/orfnormalise` (one invocation per caller-tagged input;\n     dispatch by the per-record `caller` val) - reconciles each\n     caller's native output table into a unified BED12 + sidecar TSV.\n  2. `custom/orfmerge` (one cohort-level invocation) - class-aware\n     clustering of normalised calls across callers and samples.\n  3. `bedtools/getfasta` + `seqkit/translate` - lifts the merged BED12\n     into a catalogue AA FASTA.\n  4. `mmseqs/easycluster` + `custom/orfcollapse` (optional, `val_collapse`) -\n     clusters catalogue peptides by amino-acid identity and folds duplicate\n     small ORFs to one representative each.\n\nThe collapse identity threshold defaults to `--min-seq-id 0.9` (the GENCODE\nRibo-seq ORF catalogue convention; Mudge et al. 2022), set on\n`MMSEQS_EASYCLUSTER` in this subworkflow's `nextflow.config`. Override it via\n`ext.args` on `MMSEQS_EASYCLUSTER` in the consuming pipeline's config if a\ndifferent cutoff is wanted.\n\nSupports five callers via the per-record `caller` val: ribocode, ribotish,\nribotricer, rpbp, price. Any subset can be supplied. When `ch_orf_tables` is empty\nthe subworkflow short-circuits the merge + FASTA chain and the output\nchannels are empty.\n\nOutput meta is hardcoded to `[ id: 'cohort' ]`; downstream consumers that\nwant a different cohort id should `.map` the emitted channels or\noverride `ext.prefix` on `CUSTOM_ORFMERGE` / `BEDTOOLS_GETFASTA` /\n`SEQKIT_TRANSLATE` to control output filenames. (tools: orftable_fasta_gtf_buildorfcatalogue)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"dotseq_dotseq": null, "custom_orfcollapse": null, "orftable_fasta_gtf_buildorfcatalogue": null, "pigz_uncompress": null, "caddsv_get": null}}, "target": "orftable_fasta_gtf_buildorfcatalogue", "target_idx": 2}
{"id": "mod_metaphlan_mergemetaphlantables_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merges output abundance tables from MetaPhlAn4 (tools: metaphlan4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bwa/index": "Create BWA index for reference genome", "binette": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning", "metaphlan/mergemetaphlantables": "Merges output abundance tables from MetaPhlAn4", "bracken/combinebrackenoutputs": "Combine output of metagenomic samples analyzed by bracken.", "rseqc/splitbam": "Split BAM file based on gene list in BED format"}}, "target": "metaphlan/mergemetaphlantables", "target_idx": 2}
{"id": "qc_adapt_qc_aggregate_2_28", "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": "local_subworkflow_checkirma_0_0", "category": "subworkflow_packaging", "state": {"subworkflow": "CHECKIRMA", "modules": ["custom/checkirma"], "description": "Custom validation of assembly output"}, "question": {"type": "choice", "instructions": "How should CHECKIRMA (custom/checkirma) be built?", "criteria": {"Use nf-core subworkflow checkirma": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow CHECKIRMA": null}}, "target": "Local subworkflow CHECKIRMA", "target_idx": 3}
{"id": "field_constraint_phenotype_0_2", "category": "samplesheet_schema", "state": {"field_name": "phenotype", "datatype": "pedigree_phenotype_enum", "description": "Affection status in clinical trio / family analysis"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'phenotype'?", "criteria": {"format: file-path": null, "enum: [normal, tumor]": null, "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null, "type: string free-text": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 2}
{"id": "subworkflow_pkg_vcf_annotate_ensemblvep_snpeff_3", "category": "subworkflow_packaging", "state": {"subworkflow": "VCF_ANNOTATE_ENSEMBLVEP_SNPEFF", "modules": ["ensemblvep/download", "ensemblvep/vep", "snpeff/download", "snpeff/snpeff", "htslib/bgziptabix", "bcftools/pluginscatter", "bcftools/concat", "bcftools/sort"], "description": "Perform annotation with ensemblvep and/or snpeff and bgzip + tabix index the resulting VCF file. This subworkflow uses the scatter-gather method to run VEP/snpEff in parallel to increase throughput. The input VCF is split into multiple smaller VCFs of fixed size, which are annotated separately and concatenated back together to a single output file per sample. Only VCF/BCF outputs are currently supported."}, "question": {"type": "choice", "instructions": "How should VCF_ANNOTATE_ENSEMBLVEP_SNPEFF (ensemblvep/download, ensemblvep/vep, snpeff/download, snpeff/snpeff, htslib/bgziptabix, bcftools/pluginscatter, bcftools/concat, bcftools/sort) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow VCF_ANNOTATE_ENSEMBLVEP_SNPEFF": null, "Use nf-core subworkflow vcf_annotate_ensemblvep_snpeff": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow vcf_annotate_ensemblvep_snpeff", "target_idx": 2}
{"id": "mod_atlas_pmd_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Estimate the post-mortem damage patterns of DNA (tools: atlas)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samtools/calmd": "calculates MD and NM tags", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "bam_telomere_estimation": "Estimate telomere length and content from aligned reads using telseq, telogator2, and telomerehunter", "atlas/pmd": "Estimate the post-mortem damage patterns of DNA", "leehom": "Bayesian reconstruction of ancient DNA fragments"}}, "target": "atlas/pmd", "target_idx": 3}
{"id": "subworkflow_pkg_fastq_align_bamcmp_bwa_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_ALIGN_BAMCMP_BWA", "modules": ["bamcmp", "bwa/mem", "bwa/align", "samtools/sort", "samtools/index", "samtools/stats", "samtools/idxstats", "samtools/flagstat", "bam_sort_stats_samtools"], "description": "Align reads to two different reference genomes using bwa, then use bamcmp to keep only reads that align better to the first genome, then sort with samtools"}, "question": {"type": "choice", "instructions": "How should FASTQ_ALIGN_BAMCMP_BWA (bamcmp, bwa/mem, bwa/align, samtools/sort, samtools/index, samtools/stats, samtools/idxstats, samtools/flagstat, bam_sort_stats_samtools) be structured in DSL2?", "criteria": {"Leave them out": null, "Use nf-core subworkflow fastq_align_bamcmp_bwa": null, "Keep the modules in the main workflow": null, "Local subworkflow FASTQ_ALIGN_BAMCMP_BWA": null}}, "target": "Use nf-core subworkflow fastq_align_bamcmp_bwa", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_1_17", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "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": "field_constraint_strandedness_0_3", "category": "samplesheet_schema", "state": {"field_name": "strandedness", "datatype": "categorical_enum", "description": "Library strandedness orientation in RNA-seq protocols"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'strandedness'?", "criteria": {"pattern: ^[0-9]+$": null, "type: boolean": null, "enum: [auto, forward, reverse, unstranded]": null, "format: file-path": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 2}
{"id": "mod_octopusv_correct_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Standardize a caller VCF into OctopuSV SVCF format. (tools: octopusv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"severus": null, "octopusv/correct": null, "svtools/vcftobedpe": null, "segul/aligntrim": null, "fastani": null}}, "target": "octopusv/correct", "target_idx": 1}
{"id": "samplesheet_arch_faire_seq_chromatin_2_0", "category": "samplesheet_schema", "state": {"technology": "Epigenomics", "workflow_entry": "FASTQC", "library_inputs": "Formaldehyde-assisted isolation of regulatory elements paired-end FASTQs"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,bed": null, "sample,fastq_1,fastq_2": null, "sample,bam,bai": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "schema_std_proteinfamilies_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/proteinfamilies. Description: Generation and updating of protein families.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/proteinfamilies.", "criteria": {"sample,fastq_1,fastq_2,fasta,run_accession": null, "sample_id,img_directory,parameter_file": null, "sample,fasta,existing_hmms_to_update,existing_msas_to_update": null, "sample_id,subject_id,species,pcr_target_locus,tissue": null}}, "target": "sample,fasta,existing_hmms_to_update,existing_msas_to_update", "target_idx": 2}
{"id": "mod_circularmapper_realignsamfile_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Realign reads mapped with BWA to elongated reference genome (tools: circularmapper)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bbmap_index": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode.", "bcftools_plotvcfstats": "Plots the output of bcftools stats", "circularmapper_realignsamfile": "Realign reads mapped with BWA to elongated reference genome", "umitools_extract": "Extracts UMI barcode from a read and add it to the read name, leaving any sample barcode in place", "bismark_align": "Performs alignment of BS-Seq reads using bismark"}}, "target": "circularmapper_realignsamfile", "target_idx": 2}
{"id": "resource_bbmap_sendsketch_2", "category": "resource_profiling", "state": {"process": "BBMAP_SENDSKETCH", "tool": "bbmap/sendsketch", "description": "Compares query sketches to reference sketches hosted on a remote server via the Internet."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_SENDSKETCH (Compares query sketches to reference sketches hosted on a remote server via the ) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_smartseq_plate_based_1_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": "Which columns should the samplesheet have for Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq?", "criteria": {"plate,well,sample,fastq_1,fastq_2": null, "plate,sample,bam": null, "sample,matrix": null, "sample,well,fastq": null}}, "target": "plate,well,sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "core_tool_star_bare_0", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Splice-aware alignment of paired-end RNA-seq reads against human genome GRCh38 generating coordinate-sorted BAM files.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"star": null, "bowtie2": null, "minimap2": null, "bwa_mem": null, "salmon": null}}, "target": "star", "target_idx": 0}
{"id": "qc_adapt_pacbio_hifi_1_47", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "qc_adapt_targeted_amplicon_0_34", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_semibin_singleeasybin_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: metagenomic binning with self-supervised learning (tools: semibin)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"msisensorpro/baseline": "MSIsensor-pro/baseline builds a baseline microsatellite file from a panel of normal samples, for use with msis", "biobambam/bamsormadup": "Parallel sorting and duplicate marking", "clame": "binning of metagenomic sequences", "semibin/singleeasybin": "metagenomic binning with self-supervised learning", "concoct/concoctcoveragetable": "Generate the input coverage table for CONCOCT using a BEDFile"}}, "target": "semibin/singleeasybin", "target_idx": 3}
{"id": "mod_muscle_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. A range of options are provided that give you the choice of optimizing accuracy, speed, or some compromise between the two (tools: muscle)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"emboss/cons": "cons calculates a consensus sequence from a multiple sequence alignment. To obtain the consensus, the sequence", "clustalo/align": "Align sequences using Clustal Omega", "agat/convertspgff2gtf": "Converts a GFF/GTF file into a proper GTF file", "muscle": "MUSCLE is a program for creating multiple alignments of amino acid or nucleotide sequences. A range of options", "openms/psmfeatureextractor": "Computes extra features for each input PSM for use with Percolator rescoring."}}, "target": "muscle", "target_idx": 3}
{"id": "resource_bamtools_convert_2", "category": "resource_profiling", "state": {"process": "BAMTOOLS_CONVERT", "tool": "bamtools/convert", "description": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMTOOLS_CONVERT (BamTools provides both a programmer's API and an end-user's toolkit for handling) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "pipe_all101_demultiplex_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: 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": {"viralrecon": null, "mcmicro": null, "rnastructurome": null, "demultiplex": null, "metatdenovo": null}}, "target": "demultiplex", "target_idx": 3}
{"id": "samplesheet_arch_taxprofiler_shotgun_5_2", "category": "samplesheet_schema", "state": {"assay": "Multi-taxonomic profiling of complex metagenomic shotgun reads", "first_step": "FASTQC", "inputs": "Short or long reads with run accession and library instrument platform", "pipeline": "nf-core/taxprofiler"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/taxprofiler, determine the input samplesheet column structure for: Multi-taxonomic profiling of complex metagenomic shotgun reads.", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,run_accession,instrument_platform,fastq_1,fastq_2": null, "sample,kraken_db": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 2}
{"id": "samplesheet_arch_bulk_wgs_pe_2_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Standard Paired-end Whole Genome Sequencing (WGS). Input files: Raw paired-end Illumina WGS FASTQs.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,fastq_1": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "subworkflow_pkg_gtf_hybridmerge_gffcompare_1", "category": "subworkflow_packaging", "state": {"subworkflow": "GTF_HYBRIDMERGE_GFFCOMPARE", "modules": ["gffcompare", "gawk", "bedtools/intersect"], "description": "Build a hybrid GTF by classifying a novel-transcript GTF against a reference"}, "question": {"type": "choice", "instructions": "How should GTF_HYBRIDMERGE_GFFCOMPARE (gffcompare, gawk, bedtools/intersect) be structured in DSL2?", "criteria": {"Use nf-core subworkflow gtf_hybridmerge_gffcompare": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow GTF_HYBRIDMERGE_GFFCOMPARE": null}}, "target": "Use nf-core subworkflow gtf_hybridmerge_gffcompare", "target_idx": 0}
{"id": "noul_exit_code_137_cause_14", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"An exit code of 137 in a containerized Nextflow task is typically caused by a missing shell command.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_fastqc_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run FastQC on sequenced reads (tools: fastqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"busco/generateplot": "BUSCO plot generation tool", "fastqc": "Run FastQC on sequenced reads", "biscuit/qc": "Perform basic quality control on a BAM file generated with Biscuit", "diann": "Generic DIA-NN module for running any DIA-NN operation including in-silico library generation, preliminary ana", "fgbio/zipperbams": "FGBIO tool to zip together an unmapped and mapped BAM to transfer metadata into the output BAM"}}, "target": "fastqc", "target_idx": 1}
{"id": "mod_rundbcan_easycgc_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: CGC annotation module for the dbcan pipeline. This module is used to annotate carbohydrate-active enzymes (CAZymes) from genomic data using the dbCAN annotation tool. (tools: dbcan)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_pluginfilltags": "Compute and fill various INFO tags", "odgi_build": "Construct a dynamic succinct variation graph in ODGI format from a GFAv1.", "rundbcan_database": "command from run_dbcan to prepare the database for dbCAN annotation.", "rundbcan_easycgc": "CGC annotation module for the dbcan pipeline. This module is used to annotate carbohydrate-active enzymes (CAZ", "aria2": "CLI Download utility"}}, "target": "rundbcan_easycgc", "target_idx": 3}
{"id": "qc_adapt_bulk_multiqc_1_32", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Drop MultiQC": null, "Keep FastQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "mod_porechop_abi_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extension of Porechop whose purpose is to process adapter sequences in ONT reads. (tools: porechop_abi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"porechop/abi": "Extension of Porechop whose purpose is to process adapter sequences in ONT reads.", "angsd/gl": "Calculated genotype likelihoods from BAM files.", "cutadapt": "Removes adapter sequences from sequencing reads", "artic/aligntrim": "Standalone version of fieldbioinformatics aligntrim. Soft clips amplicon scheme primer sites in BAM/SAM files.", "bcftools/pluginfilltags": "Compute and fill various INFO tags"}}, "target": "porechop/abi", "target_idx": 0}
{"id": "pipe_all101_eager_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze A fully reproducible and state-of-the-art ancient DNA analysis pipeline. Topics: adna, ancient-dna-analysis, ancientdna, genome, metagenomics, pathogen-genomics. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"airrflow": "B-cell and T-cell Adaptive Immune Receptor Repertoire (AIRR) sequencing analysis pipeline using the Immcantation framewo", "multiplesequencealign": "A pipeline to run and systematically evaluate Multiple Sequence Alignment (MSA) methods.", "denovotranscript": "A pipeline for de novo transcriptome assembly of paired-end short reads from bulk RNA-seq [denovo-assembly, rna-seq, tra", "rnavar": "gatk4 RNA variant calling pipeline [gatk4, rna, rnaseq]", "seqsubmit": "nf-core pipeline for data submission to ENA", "callingcards": "A pipeline for processing calling cards data", "funcscan": "(Meta-)genome screening for functional and natural product gene sequences [amp, amr, antibiotic-resistance]", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline [adna, ancient-dna-analysis, ancientdna]", "metapep": "From metagenomes to epitopes and beyond", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 [16s, 18s, amplicon-sequencing]"}}, "target": "eager", "target_idx": 7}
{"id": "samplesheet_arch_viral_ont_single_4_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": "What samplesheet columns are expected when inputs are: Demultiplexed single-end long reads from tiled viral amplicons?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,fasta": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1", "target_idx": 1}
{"id": "pipe_all101_hicar_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Pipeline for HiCAR data, a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chromatin accessibility and cis-regulatory chromatin contacts.. Topics: atac, atac-seq, hic, hicar, multi-omics, transcriptome. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"funcprofiler": "Read-based functional profiling of microbiome sequencing data", "createpanelrefs": "Generate Panel of Normals, models or other similar references from lots of samples", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "hicar": "Pipeline for HiCAR data, a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chrom", "funcscan": "(Meta-)genome screening for functional and natural product gene sequences [amp, amr, antibiotic-resistance]"}}, "target": "hicar", "target_idx": 3}
{"id": "qc_adapt_ont_ultra_long_0_27", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "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": "samplesheet_arch_dual_rnaseq_host_pathogen_6_5", "category": "samplesheet_schema", "state": {"assay": "Dual RNA-seq simultaneous host and pathogen transcriptomics", "first_step": "FASTQC", "inputs": "Paired-end FASTQs from infected tissue undergoing dual mapping to human and pathogen"}, "question": {"type": "choice", "instructions": "Which columns are standard for Dual RNA-seq simultaneous host and pathogen transcriptomics input samplesheet?", "criteria": {"sample,fastq_1,fastq_2,host,pathogen": null, "sample,fastq_1": null, "sample,bam": null, "sample,host_fasta": null}}, "target": "sample,fastq_1,fastq_2,host,pathogen", "target_idx": 0}
{"id": "mod_orthofinder_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: OrthoFinder is a fast, accurate and comprehensive platform for comparative genomics. (tools: orthofinder)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"regenie/step1": null, "agat/spflagshortintrons": null, "orthofinder": null, "agat/spfilterfeaturefromkilllist": null, "ssuissero": null}}, "target": "orthofinder", "target_idx": 2}
{"id": "mod_samtools_import_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: converts FASTQ files to unmapped SAM/BAM/CRAM (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"adapterremovalfixprefix": "Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with", "samtools_import": "converts FASTQ files to unmapped SAM/BAM/CRAM", "ivar_consensus": "Generate a consensus sequence from a BAM file using iVar", "truvari_bench": "Given baseline and comparison sets of variants, calculate the recall/precision/f-measure", "art_illumina": "Simulation tool to generate synthetic Illumina next-generation sequencing reads"}}, "target": "samtools_import", "target_idx": 1}
{"id": "field_constraint_status_0_12", "category": "samplesheet_schema", "state": {"field_name": "status", "datatype": "somatic_status_enum", "description": "Tissue status for somatic cancer workflows"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'status'?", "criteria": {"format: file-path": null, "enum: [0, 1] (0=normal, 1=tumor)": null, "pattern: ^[A-Z]+$": null, "enum: [auto, forward, reverse]": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 1}
{"id": "mod_bio2zarr_vcf2zarrexplode_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert VCF(s) to intermediate columnar format (ICF) (tools: vcf2zarr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_annotate": "Add or remove annotations.", "atlas_call": "generate VCF file from a BAM file using various calling methods", "rseqc_junctionsaturation": "compare detected splice junctions to reference gene model", "graphmap2_align": "A versatile pairwise aligner for genomic and spliced nucleotide sequences", "bio2zarr_vcf2zarrexplode": "Convert VCF(s) to intermediate columnar format (ICF)"}}, "target": "bio2zarr_vcf2zarrexplode", "target_idx": 4}
{"id": "samplesheet_arch_epigenomics_hic_3_0", "category": "samplesheet_schema", "state": {"assay": "Hi-C chromosome conformation capture mapping", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Hi-C chromosome conformation capture mapping with entry step FASTQC.", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bed": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "samplesheet_arch_metagenome_mag_grouped_6_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 are standard for Metagenomic MAG assembly with comparative groups input samplesheet?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 2}
{"id": "qc_adapt_targeted_amplicon_0_0", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "resource_bcftools_pluginsetgt_2", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINSETGT", "tool": "bcftools/pluginsetgt", "description": "Sets genotypes according to the specified criteria and filtering expressions. For example, missing genotypes can be set to ref, but much more than that."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINSETGT (Sets genotypes according to the specified criteria and filtering expressions. Fo) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "schema_std_molkart_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/molkart. Description: A pipeline for processing Molecular Cartography data from Resolve Bioscience (combinatorial FISH).", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/molkart.", "criteria": {"sample_id,group_id,subject_id,sample_type,sequence_type": null, "sample,fastq_1,fastq_2,strandedness,condition": null, "sample,nuclear_image,spot_table,membrane_image": null, "id,path": null}}, "target": "sample,nuclear_image,spot_table,membrane_image", "target_idx": 2}
{"id": "field_constraint_expected_cells_2_10", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'expected_cells' (Expected cell count in single-cell droplet pipelines) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'expected_cells' validated?", "criteria": {"pattern: ^\\S+\\.csv$": null, "format: file-path": null, "type: integer, minimum: 100, maximum: 50000": null, "enum: [auto, single, paired]": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 2}
{"id": "pipe_all101_pairgenomealign_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plot the results. Topics: comparative-genomics, dot-plot, genomics, last, pairwise-alignment, synteny. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"magmap": null, "pairgenomealign": null, "callingcards": null, "rnaseq": null, "rnastructurome": null, "slamseq": null, "viralintegration": null, "lsmquant": null, "rnafusion": null, "detaxizer": null}}, "target": "pairgenomealign", "target_idx": 1}
{"id": "mod_biscuit_vcf2bed_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Summarizes methylation or SNV information from a Biscuit VCF in a\nstandard-compliant BED file. (tools: biscuit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"krona_ktupdatetaxonomy": "KronaTools Update Taxonomy downloads a taxonomy database", "biscuit_vcf2bed": "Summarizes methylation or SNV information from a Biscuit VCF in a\nstandard-compliant BED file.", "myloasm": "Myloasm is a de novo metagenome assembler for long-read sequencing data.\nIt takes sequencing reads and outputs", "biscuit_index": "Indexes a reference genome for use with Biscuit", "biscuit_bsconv": "Summarize and/or filter reads based on bisulfite conversion rate"}}, "target": "biscuit_vcf2bed", "target_idx": 1}
{"id": "qc_adapt_ont_ultra_long_0_3", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "samplesheet_arch_pediatric_trio_somatic_2_0", "category": "samplesheet_schema", "state": {"technology": "Clinical Genetics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end FASTQs tracking patient, sample, tissue status (normal/tumor), and maternal/paternal lineage"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"family_id,sample,fastq_1,fastq_2": null, "family_id,patient,sample,status,sex,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null}}, "target": "family_id,patient,sample,status,sex,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_fasta_clean_fcs_1", "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": {"tiddit_sv": null, "agrvate": null, "fasta_clean_fcs": null, "fcsgx_cleangenome": null, "drep_dereplicate": null}}, "target": "fasta_clean_fcs", "target_idx": 2}
{"id": "mod_csvtk_concat_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Concatenate two or more CSV (or TSV) tables into a single table (tools: csvtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"caalm/downloadmodels": "Downloads the CAALM model weights from HuggingFace Hub (lczong/CAALM) into a\nlocal models/ directory. The down", "cat/fastq": "Concatenates fastq files. Supports both compressed (.gz) and uncompressed inputs; uncompressed files are autom", "graphtyper/vcfconcatenate": "Tools for population-scale genotyping using pangenome graphs.", "variantbam": "Filtering, downsampling and profiling alignments in BAM/CRAM formats", "csvtk/concat": "Concatenate two or more CSV (or TSV) tables into a single table"}}, "target": "csvtk/concat", "target_idx": 4}
{"id": "samplesheet_arch_bulk_small_rna_1_5", "category": "samplesheet_schema", "state": {"assay": "Small RNA / miRNA sequencing", "first_step": "FASTQC", "template": "nf-core/smrnaseq"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Small RNA / miRNA sequencing?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "resource_busco_plot_5", "category": "resource_profiling", "state": {"process": "BUSCO_PLOT", "tool": "busco/plot", "description": "BUSCO summary plot generation using the built-in 'busco --plot' command"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BUSCO_PLOT (BUSCO summary plot generation using the built-in 'busco --plot' command) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_angsd_dosaf_0", "category": "resource_profiling", "state": {"process": "ANGSD_DOSAF", "tool": "angsd/dosaf", "description": "Estimate site allele frequencies from BAM files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANGSD_DOSAF (Estimate site allele frequencies from BAM files.) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_ont_metagenome_single_1_4", "category": "samplesheet_schema", "state": {"assay": "Long-read Oxford Nanopore environmental metagenomic sequencing", "first_step": "NANOPLOT"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Long-read Oxford Nanopore environmental metagenomic sequencing?", "criteria": {"sample,fasta": null, "sample,bam": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,group": null}}, "target": "sample,fastq_1,group", "target_idx": 3}
{"id": "mod_svdss_index_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Index a reference genome FASTA file using SVDSS (via ropebwt3), producing either an FMD or FMR index for use with SVDSS smooth and search subcommands (tools: svdss)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"freyja/demix": "specify the relative abundance of each known haplotype", "annotsv/annotsv": "Annotation and Ranking of Structural Variation", "caddsv/run": "Score structural variants with CADD-SV.", "hapibd": "The hap-ibd program detects identity-by-descent (IBD) segments and homozygosity-by-descent (HBD) segments in p", "svdss/index": "Index a reference genome FASTA file using SVDSS (via ropebwt3), producing either an FMD or FMR index for use w"}}, "target": "svdss/index", "target_idx": 4}
{"id": "samplesheet_arch_cancer_somatic_bam_8_1", "category": "samplesheet_schema", "state": {"assay": "Somatic tumor-normal calling from pre-aligned BAM files", "first_step": "MUTECT2", "inputs": "Coordinate-sorted BAMs with index for tumor and normal samples"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for BAM inputs?", "criteria": {"patient,sample,status,bam,bai": null, "sample,vcf": null, "sample,bam,bai": null, "patient,sample,bam": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 0}
{"id": "samplesheet_arch_ont_direct_rna_se_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/nanoseq", "assay_type": "Single-end Oxford Nanopore direct RNA", "data_format": "Single fastq per sample"}, "question": {"type": "choice", "instructions": "Which columns are standard for Single-end Oxford Nanopore direct RNA input samplesheet?", "criteria": {"sample,bam": null, "sample,fast5": null, "sample,vcf": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "mod_cleanifier_filter_1", "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": {"cleanifier_download": null, "cleanifier_filter": null, "binette": null, "plink_hwe": null, "mafft_align": null}}, "target": "cleanifier_filter", "target_idx": 1}
{"id": "schema_std_methylseq_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/methylseq. Description: Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/methylseq.", "criteria": {"patient,vcf,tbi,dataset,tumour_sample": null, "sample,fastq_1,fastq_2,genome": null, "sample,run,group,short_reads_1,short_reads_2": null, "sample,fastq_1,fastq_2,bam,seq_type": null}}, "target": "sample,fastq_1,fastq_2,genome", "target_idx": 1}
{"id": "mod_souporcell_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: souporcell is a method for clustering mixed-genotype scRNAseq experiments by individual. (tools: souporcell)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"comebin_runcomebin": "Effective binning of metagenomic contigs using COntrastive Multi-viEw representation learning", "souporcell": "souporcell is a method for clustering mixed-genotype scRNAseq experiments by individual.", "diamond_deepclust": "Fast graph-based protein sequence clustering using DIAMOND deepclust", "ampcombi2_cluster": "A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete usin", "bamutil_clipoverlap": "clips overlapping read pairs. When two mates overlap, this tool will clip the record's whose clipped region wo"}}, "target": "souporcell", "target_idx": 1}
{"id": "qc_adapt_qc_aggregate_2_18", "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_staramr_search_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Scans genome contigs against the ResFinder, PlasmidFinder, and PointFinder databases. (tools: staramr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bismark_coverage2cytosine": "Relates methylation calls back to genomic cytosine contexts.", "staramr_search": "Scans genome contigs against the ResFinder, PlasmidFinder, and PointFinder databases.", "hamronization_deeparg": "Tool to convert and summarize DeepARG outputs using the hAMRonization specification", "atlas_pmd": "Estimate the post-mortem damage patterns of DNA", "hamronization_abricate": "Tool to convert and summarize ABRicate outputs using the hAMRonization specification"}}, "target": "staramr_search", "target_idx": 1}
{"id": "mod_ltrretriever_lai_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Estimates the mean LTR sequence identity in the genome. The input genome fasta should\nhave short alphanumeric IDs without comments (tools: lai)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ltrretriever_lai": null, "agat_spmergeannotations": null, "happy_sompy": null, "mmseqs_createtaxdb": null, "agat_spextractsequences": null}}, "target": "ltrretriever_lai", "target_idx": 0}
{"id": "samplesheet_arch_atacseq_replicates_1_3", "category": "samplesheet_schema", "state": {"assay": "ATAC-seq chromatin accessibility with biological replicates", "first_step": "FASTQC", "inputs": "Paired-end Tn5 transposed FASTQs across conditions and replicates"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for ATAC-seq chromatin accessibility with biological replicates?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2,replicate": null, "sample,bed": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 1}
{"id": "resource_art_illumina_1", "category": "resource_profiling", "state": {"process": "ART_ILLUMINA", "tool": "art/illumina", "description": "Simulation tool to generate synthetic Illumina next-generation sequencing reads"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ART_ILLUMINA (Simulation tool to generate synthetic Illumina next-generation sequencing reads) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "noul_default_empty_channel_behavior_2", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `Channel.fromPath('data/*.fq')` emits an error if no files match the wildcard pattern by default.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "resource_barrnap_4", "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_medium": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_biscuit_bsconv_1", "category": "resource_profiling", "state": {"process": "BISCUIT_BSCONV", "tool": "biscuit/bsconv", "description": "Summarize and/or filter reads based on bisulfite conversion rate"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISCUIT_BSCONV (Summarize and/or filter reads based on bisulfite conversion rate) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "schema_std_bamtofastq_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/bamtofastq", "assay": "bamtofastq pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/bamtofastq (Converts bam or cram files to fastq format and does quality )?", "criteria": {"sample_id,mapped,index,file_type": null, "SAMPLE_ID,RCC_FILE,RCC_FILE_NAME,TIME,TREATMENT": null, "sample,seed": null, "sample,group,ref_fasta,ref_gff,use_ref": null}}, "target": "sample_id,mapped,index,file_type", "target_idx": 0}
{"id": "mod_sequenzautils_gcwiggle_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sequenza-utils gc_wiggle computes the GC percentage across the sequences, and returns a file in the UCSC wiggle format, given a fasta file and a window size. (tools: sequenzautils)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cnvkit/batch": null, "cnaqc": null, "angsd/docounts": null, "sequenzautils/gcwiggle": null, "differential_functional_enrichment": null}}, "target": "sequenzautils/gcwiggle", "target_idx": 3}
{"id": "mod_ncbitools_vecscreen_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: NCBI tool for detecting vector contamination in nucleic acid sequences. This tool is older than NCBI's FCS-adaptor, which is for the same purpose (tools: ncbitools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"segemehl_index": null, "ncbitools_vecscreen": null, "abra2": null, "ale": null, "metaeuk_easypredict": null}}, "target": "ncbitools_vecscreen", "target_idx": 1}
{"id": "resource_blobtk_create_1", "category": "resource_profiling", "state": {"process": "BLOBTK_CREATE", "tool": "blobtk/create", "description": "Creates a minimal blobdir."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLOBTK_CREATE (Creates a minimal blobdir.) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_singlecell_multiqc_1_28", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "resource_amplify_predict_5", "category": "resource_profiling", "state": {"process": "AMPLIFY_PREDICT", "tool": "amplify/predict", "description": "AMPlify is an attentive deep learning model for antimicrobial peptide prediction."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMPLIFY_PREDICT (AMPlify is an attentive deep learning model for antimicrobial peptide prediction) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_eido_convert_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert any PEP project or Nextflow samplesheet to any format (tools: eido)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamtofastq10x": "Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ATAC, Cell Ranger DNA, and Lon", "eido/convert": "Convert any PEP project or Nextflow samplesheet to any format", "cat/fastq": "Concatenates fastq files. Supports both compressed (.gz) and uncompressed inputs; uncompressed files are autom", "tcoffee/align": "Aligns sequences using T_COFFEE", "eido/validate": "Validate samplesheet or PEP config against a schema"}}, "target": "eido/convert", "target_idx": 1}
{"id": "subworkflow_pkg_mmseqs_fasta_cluster_0", "category": "subworkflow_packaging", "state": {"subworkflow": "MMSEQS_FASTA_CLUSTER", "modules": ["mmseqs/createdb", "mmseqs/cluster", "mmseqs/linclust", "mmseqs/createtsv"], "description": "Subworkflow that generates a clustering TSV file from a set of amino acid sequence within a FASTA file."}, "question": {"type": "choice", "instructions": "How should MMSEQS_FASTA_CLUSTER (mmseqs/createdb, mmseqs/cluster, mmseqs/linclust, mmseqs/createtsv) be structured in DSL2?", "criteria": {"Use nf-core subworkflow mmseqs_fasta_cluster": null, "Keep the modules in the main workflow": null, "Local subworkflow MMSEQS_FASTA_CLUSTER": null, "Leave them out": null}}, "target": "Use nf-core subworkflow mmseqs_fasta_cluster", "target_idx": 0}
{"id": "mod_hostile_clean_1", "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": {"alignoth": "Creating alignment plots from bam files", "hostile_clean": "Removes host reads from short- and long-read FASTQ sequencing files", "cutadapt": "Removes adapter sequences from sequencing reads", "fastq_fetch_clean_hostile": "Downloads required reference genomes for hostile and removes host reads from short-read FASTQ sequencing files", "hostile_fetch": "Downloads required reference genomes for Hostile"}}, "target": "hostile_clean", "target_idx": 1}
{"id": "mod_hmmer_jackhmmer_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: iterative searches to detect distant homologs by refining an HMM profile from hits (tools: hmmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"openms/fileconverter": "Converts between different mass spectrometry file formats (e.g. mzML, mzXML, mgf, mzData, dta, dta2d, featureX", "hmmer/hmmbuild": "create an hmm profile from a multiple sequence alignment", "hifiadapterfilt/downloaddb": "Downloads the pre-built PacBio adapter BLAST database from the HiFiAdapterFilt\nGitHub repository. The database", "hhsuite/hhblits": "Fast and sensitive protein sequence searching based on the pairwise alignment of hidden Markov models (HMMs)", "hmmer/jackhmmer": "iterative searches to detect distant homologs by refining an HMM profile from hits"}}, "target": "hmmer/jackhmmer", "target_idx": 4}
{"id": "pipe_all101_proteinannotator_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for annotation analysis? Specific context: Generation of sequence-level annotations for amino acid sequences. Topics: annotation, proteomics. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"nascent": "Nascent Transcription Processing Pipeline [gro-seq, nascent, pro-seq]", "hlatyping": "Precision HLA typing from next-generation sequencing data [dna, hla, hla-typing]", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples [amplicon, artic, assembly]", "metatdenovo": "Assembly and annotation of metatranscriptomic or metagenomic data for prokaryotic, eukaryotic and viruses. [eukaryotes, ", "differentialabundance": "Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq  [atac-seq, chip-seq, d", "proteinannotator": "Generation of sequence-level annotations for amino acid sequences [annotation, proteomics]", "mnaseseq": "MNase-seq analysis pipeline using BWA and DANPOS2. [mnase-seq, nucleosome, nucleosome-maps]", "hic": "Analysis of Chromosome Conformation Capture data (Hi-C) [chromosome-conformation-capture, hi-c]"}}, "target": "proteinannotator", "target_idx": 5}
{"id": "mod_sequencetools_pileupcaller_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: PileupCaller is a tool to create genotype calls from bam files using read-sampling methods (tools: sequencetools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hipstr": "Genotype and phase short tandem repeats using Illumina whole-genome sequencing data", "bwafastalign/index": "Create BWA-FASTALIGN index for reference genome", "pypgx/runngspipeline": "PyPGx pharmacogenomics genotyping pipeline for NGS data.", "sequencetools/pileupcaller": "PileupCaller is a tool to create genotype calls from bam files using read-sampling methods", "umitools/group": "Group reads based on their UMI and mapping coordinates"}}, "target": "sequencetools/pileupcaller", "target_idx": 3}
{"id": "samplesheet_arch_bulk_rnaseq_se_6_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/rnaseq) for Single-end Illumina RNA-seq with strandedness. Input files: Single-end FASTQ reads per library.", "question": {"type": "choice", "instructions": "Which columns are standard for Single-end Illumina RNA-seq with strandedness input samplesheet?", "criteria": {"sample,fastq_1,fastq_2,strandedness": null, "sample,vcf": null, "sample,bam": null, "sample,fastq_1,strandedness": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 3}
{"id": "mod_fgbio_collectduplexseqmetrics_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Collects a suite of metrics to QC duplex sequencing data. (tools: fgbio)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgumi/correct": null, "fgbio/collectduplexseqmetrics": null, "splitubam": null, "fgumi/downsample": null, "lofreq/indelqual": null}}, "target": "fgbio/collectduplexseqmetrics", "target_idx": 1}
{"id": "qc_adapt_bulk_multiqc_0_29", "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": "samplesheet_arch_scrna_multiome_4_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/scrnaseq", "assay_type": "10x Multiome single-cell joint RNA and ATAC chromatin", "data_format": "Paired FASTQs for both GEX and ATAC modalities per nucleus"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired FASTQs for both GEX and ATAC modalities per nucleus?", "criteria": {"sample,bam": null, "sample,matrix": null, "sample,fastq_1,fastq_2,feature_type": null, "sample,rna_fastq,atac_fastq": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 2}
{"id": "qc_adapt_ffpe_wes_0_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": "For Degraded FFPE exome capture sequencing on Illumina, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "noul_mix_operator_async_emission_20", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.mix()` channel operator waits until all source channels have completed before emitting any items.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_bulk_rnaseq_pe_5_3", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq with strandedness", "first_step": "FASTQC", "inputs": "Paired-end FASTQ reads with library strandedness"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/rnaseq, determine the input samplesheet column structure for: Paired-end Illumina RNA-seq with strandedness.", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,bam": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 2}
{"id": "samplesheet_arch_cancer_tumor_only_4_3", "category": "samplesheet_schema", "state": {"assay": "Tumor-only somatic variant calling without matched normal", "first_step": "FASTQC", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end FASTQ reads from tumor biopsy without matched normal?", "criteria": {"sample,bam": null, "patient,normal,tumor": 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": "qc_adapt_ffpe_wes_2_19", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "resource_bcftools_merge_3", "category": "resource_profiling", "state": {"process": "BCFTOOLS_MERGE", "tool": "bcftools/merge", "description": "Merge VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_MERGE (Merge VCF files) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_skani_dist_0", "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": {"malt/build": null, "skani/dist": null, "skani/triangle": null, "skani/search": null, "bbmap/clumpify": null}}, "target": "skani/dist", "target_idx": 1}
{"id": "mod_blobtk_plot_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Creates differing styles of blobplots depending on provided arguments. (tools: blobtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"blobtk_plot": null, "mcquant": null, "pretextsnapshot": null, "pbptyper": null, "chromograph": null}}, "target": "blobtk_plot", "target_idx": 0}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/rnaseq) for Paired-end Illumina RNA-seq. Input files: FastQ reads per sample.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Paired-end Illumina RNA-seq?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "samplesheet_arch_cutandrun_pe_4_1", "category": "samplesheet_schema", "state": {"assay": "CUT&RUN / CUT&TAG chromatin profiling with IgG control", "first_step": "FASTQC", "inputs": "Paired-end low-input fragment FASTQs with target antibody and IgG negative control"}, "question": {"type": "choice", "instructions": "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,spikein,fastq": null, "sample,fastq_1,fastq_2,target,control": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 3}
{"id": "resource_ampcombi2_parsetables_3", "category": "resource_profiling", "state": {"process": "AMPCOMBI2_PARSETABLES", "tool": "ampcombi2/parsetables", "description": "A submodule that parses and standardizes the results from various antimicrobial peptide identification tools."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMPCOMBI2_PARSETABLES (A submodule that parses and standardizes the results from various antimicrobial ) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "subworkflow_pkg_bam_impute_quilt_0", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_IMPUTE_QUILT", "modules": ["gawk", "quilt/quilt", "bcftools/index", "glimpse2/ligate"], "description": "Subworkflow to impute BAM files using QUILT software."}, "question": {"type": "choice", "instructions": "How should BAM_IMPUTE_QUILT (gawk, quilt/quilt, bcftools/index, glimpse2/ligate) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow BAM_IMPUTE_QUILT": null, "Use nf-core subworkflow bam_impute_quilt": null}}, "target": "Use nf-core subworkflow bam_impute_quilt", "target_idx": 3}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_4_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/rnaseq", "assay_type": "Paired-end Illumina RNA-seq", "data_format": "FastQ reads per sample"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: FastQ reads per sample?", "criteria": {"sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_nanoq_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Nanoq implements ultra-fast read filters and summary reports for high-throughput nanopore reads. (tools: nanoq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"holodeck_methylate": null, "macrel_contigs": null, "lsa_cosine": null, "nanoq": null, "ribodetector": null}}, "target": "nanoq", "target_idx": 3}
{"id": "resource_bcftools_plugintag2tag_4", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINTAG2TAG", "tool": "bcftools/plugintag2tag", "description": "Converts between similar tags, such as GL,PL,GP or QR,QA,QS or localized alleles, eg LPL,LAD."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINTAG2TAG (Converts between similar tags, such as GL,PL,GP or QR,QA,QS or localized alleles) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_ivar_variants_0", "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": {"clipkit": null, "freyja/boot": null, "ivar/variants": null, "samtools/fastq": null, "cadd": null}}, "target": "ivar/variants", "target_idx": 2}
{"id": "samplesheet_arch_ancient_dna_eager_5_5", "category": "samplesheet_schema", "state": {"assay": "Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment", "first_step": "FASTQC", "template": "nf-core/eager"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/eager, determine the input samplesheet column structure for: Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null, "sample,library_id,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_2_29", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "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_prealigned_bam_indexed_6_0", "category": "samplesheet_schema", "state": {"technology": "Pre-aligned Assets", "workflow_entry": "GATK_HAPLOTYPECALLER", "library_inputs": "Aligned BAM files"}, "question": {"type": "choice", "instructions": "Which columns are standard for Pre-aligned BAM variant calling pipeline input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,vcf": null, "sample,bam,bai": null}}, "target": "sample,bam,bai", "target_idx": 3}
{"id": "mod_humann3_humann_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Functional analysis of metagenome or metatranscriptome data (tools: humann)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pharokka_installdatabases": "Install databases necessary for Pharokka's functional analysis", "humann3_humann": "Functional analysis of metagenome or metatranscriptome data", "humann3_regroup": "Regrouping genes to other functional categories", "chewbbaca_allelecall": "Determine the allelic profiles of a genome using a pre-defined schema", "fastplong": "Perform adapter/quality trimming and QC on long sequencing reads (ONT, PacBio, etc.)"}}, "target": "humann3_humann", "target_idx": 1}
{"id": "samplesheet_arch_mira_influenza_sc2_4_4", "category": "samplesheet_schema", "state": {"technology": "Viral Surveillance", "workflow_entry": "INPUT_CHECK", "library_inputs": "Paired-end surveillance FASTQs from respiratory pathogen panels"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end surveillance FASTQs from respiratory pathogen panels?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "core_tool_macs2_bare_0", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Model-based analysis of ChIP-Seq data to identify statistically significant transcription factor binding sites and histone mark enrichment peaks.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"seacr": null, "epic2": null, "homer": null, "genrich": null, "macs2": null}}, "target": "macs2", "target_idx": 4}
{"id": "qc_adapt_illumina_novaseq_2_23", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "subworkflow_pkg_bam_tumor_normal_somatic_variant_calling_gatk_0", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_TUMOR_NORMAL_SOMATIC_VARIANT_CALLING_GATK", "modules": ["gatk4/mutect2", "gatk4/learnreadorientationmodel", "gatk4/getpileupsummaries", "gatk4/calculatecontamination", "gatk4/filtermutectcalls"], "description": "Perform variant calling on a paired tumor normal set of samples using mutect2 tumor normal mode."}, "question": {"type": "choice", "instructions": "How should BAM_TUMOR_NORMAL_SOMATIC_VARIANT_CALLING_GATK (gatk4/mutect2, gatk4/learnreadorientationmodel, gatk4/getpileupsummaries, gatk4/calculatecontamination, gatk4/filtermutectcalls) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow BAM_TUMOR_NORMAL_SOMATIC_VARIANT_CALLING_GATK": null, "Use nf-core subworkflow bam_tumor_normal_somatic_variant_calling_gatk": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow bam_tumor_normal_somatic_variant_calling_gatk", "target_idx": 2}
{"id": "mod_ariba_run_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Query input FASTQs against Ariba formatted databases (tools: ariba)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ariba_run": "Query input FASTQs against Ariba formatted databases", "gatk4_calculatecontamination": "Calculates the fraction of reads from cross-sample contamination based on summary tables from getpileupsummari", "shinyngs_validatefomcomponents": "validate consistency of feature and sample annotations with matrices and contrasts", "adapterremovalfixprefix": "Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with", "adapterremoval": "Trim sequencing adapters and collapse overlapping reads"}}, "target": "ariba_run", "target_idx": 0}
{"id": "schema_std_tumourevo_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/tumourevo", "assay": "tumourevo pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/tumourevo (Analysis pipeline to model tumour clonal evolution from WGS )?", "criteria": {"sample,fastq_1,fastq_2,batch,condition": null, "patient,vcf,tbi,dataset,tumour_sample": null, "sample,fasta,protein,gbk,gff": null, "patient,sample,vcf,status,cna": null}}, "target": "patient,vcf,tbi,dataset,tumour_sample", "target_idx": 1}
{"id": "mod_regenie_splitl0_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Split REGENIE step 1 level-0 ridge-regression blocks into parallel jobs (tools: regenie)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"regenie_splitl0": "Split REGENIE step 1 level-0 ridge-regression blocks into parallel jobs", "regenie_step1": "Run REGENIE step 1 to fit whole-genome regression models and emit LOCO predictions", "regenie_runl0": "Run one REGENIE step 1 level-0 job from a split master file", "finaletoolkit_wps": "Calculate the windowed protection score (WPS; Snyder et al., 2016)\nfrom a BAM file and a list of transcription", "bwameme_mem": "Performs fastq alignment to a fasta reference using BWA-MEME"}}, "target": "regenie_splitl0", "target_idx": 0}
{"id": "samplesheet_arch_ont_demux_barcodes_2_4", "category": "samplesheet_schema", "state": {"assay": "Multiplexed Oxford Nanopore run with barcode demultiplexing", "first_step": "NANOPLOT", "inputs": "Nanopore sequencing run with sample to barcode assignment and flowcell type", "pipeline": "nf-core/nanoseq"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,barcode,flowcell,kit,fastq": null, "sample,barcode": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 1}
{"id": "samplesheet_arch_bulk_wgs_pe_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Standard Paired-end Whole Genome Sequencing (WGS))", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/sarek, determine the input samplesheet column structure for: Standard Paired-end Whole Genome Sequencing (WGS).", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "samplesheet_arch_cancer_longitudinal_4_1", "category": "samplesheet_schema", "state": {"assay": "Longitudinal cancer monitoring across multiple timepoints", "first_step": "FASTQC", "inputs": "Serial plasma cfDNA and biopsy FASTQs across treatment intervals"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Serial plasma cfDNA and biopsy FASTQs across treatment intervals?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,timepoint,fastq": null, "patient,sample,bam": null, "patient,sample,timepoint,status,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,status,fastq_1,fastq_2", "target_idx": 3}
{"id": "resource_bwa_sampe_3", "category": "resource_profiling", "state": {"process": "BWA_SAMPE", "tool": "bwa/sampe", "description": "Convert paired-end bwa SA coordinate files to SAM format"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWA_SAMPE (Convert paired-end bwa SA coordinate files to SAM format) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_single": null, "process_low": null}}, "target": "process_high", "target_idx": 0}
{"id": "subworkflow_pkg_fastq_align_dedup_bwameth_3", "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": {"Local subworkflow FASTQ_ALIGN_DEDUP_BWAMETH": null, "Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow fastq_align_dedup_bwameth": null}}, "target": "Use nf-core subworkflow fastq_align_dedup_bwameth", "target_idx": 3}
{"id": "samplesheet_arch_bulk_rnaseq_pe_2_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 should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 0}
{"id": "mod_propr_propr_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform logratio-based correlation analysis -> get proportionality & basis shrinkage partial correlation coefficients.\nOne can also compute standard correlation coefficients, if required. (tools: propr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"propr_propd": "Perform differential proportionality analysis", "pairtools_select": "Select pairs according to given condition by options.args", "propr_propr": "Perform logratio-based correlation analysis -> get proportionality & basis shrinkage partial correlation coeff", "propr_grea": "Perform Gene Ratio Enrichment Analysis", "metaspace_converter": "Export METASPACE datasets to AnnData and SpatialData objects"}}, "target": "propr_propr", "target_idx": 2}
{"id": "samplesheet_arch_ont_demux_barcodes_1_5", "category": "samplesheet_schema", "state": {"assay": "Multiplexed Oxford Nanopore run with barcode demultiplexing", "first_step": "NANOPLOT", "template": "nf-core/nanoseq"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Multiplexed Oxford Nanopore run with barcode demultiplexing?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,barcode,flowcell,kit,fastq": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 3}
{"id": "mod_cleanifier_download_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Download human reference index (tools: cleanifier)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"caalm/downloadmodels": "Downloads the CAALM model weights from HuggingFace Hub (lczong/CAALM) into a\nlocal models/ directory. The down", "cleanifier/download": "Download human reference index", "kma/kma": "Mapping raw reads directly against redundant databases via KMA alignment", "bcftools/plotvcfstats": "Plots the output of bcftools stats", "aria2": "CLI Download utility"}}, "target": "cleanifier/download", "target_idx": 1}
{"id": "mod_geofetch_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: geofetch is a command-line tool that downloads and organizes data and metadata from GEO and SRA (tools: geofetch)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"telomerehunter": "In silico estimation of telomere content and composition from cancer genomes", "geofetch": "geofetch is a command-line tool that downloads and organizes data and metadata from GEO and SRA", "nacho/normalize": "NACHO (NAnostring quality Control dasHbOard) is developed for NanoString nCounter data.\nNanoString nCounter da", "deseq2/differential": "runs a differential expression analysis with DESeq2", "ffq": "A command line tool that makes it easier to find sequencing data from the SRA / GEO / ENA."}}, "target": "geofetch", "target_idx": 1}
{"id": "resource_bwa_sampe_1", "category": "resource_profiling", "state": {"process": "BWA_SAMPE", "tool": "bwa/sampe", "description": "Convert paired-end bwa SA coordinate files to SAM format"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWA_SAMPE (Convert paired-end bwa SA coordinate files to SAM format) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_medium": null, "process_single": null}}, "target": "process_high", "target_idx": 1}
{"id": "qc_adapt_ont_nanoplot_1_13", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_custom_geneticmapconvert_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: This R script allows to automatically detect the different genetic map format and\nconvert the input file in all the other format type. (tools: custom)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gffread": "Validate, filter, convert and perform various other operations on GFF files", "skani_sketch": "Storing skani sketches/indices on disk.", "bbmap_align": "Align short or PacBio reads to a reference genome using BBMap", "custom_geneticmapconvert": "This R script allows to automatically detect the different genetic map format and\nconvert the input file in al", "bismark_align": "Performs alignment of BS-Seq reads using bismark"}}, "target": "custom_geneticmapconvert", "target_idx": 3}
{"id": "samplesheet_arch_prealigned_cram_indexed_2_0", "category": "samplesheet_schema", "state": {"technology": "Pre-aligned Assets", "workflow_entry": "GATK_HAPLOTYPECALLER", "library_inputs": "Coordinate-sorted CRAM alignments with companion CRAI indexes"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam,bai": null, "sample,cram,crai": null, "sample,cram": null}}, "target": "sample,cram,crai", "target_idx": 2}
{"id": "mod_glimpse_sample_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generates haplotype calls by sampling haplotype estimates (tools: glimpse)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mafft_align": "Multiple sequence alignment using MAFFT", "qcat": "Demultiplexer for Nanopore samples", "glimpse_sample": "Generates haplotype calls by sampling haplotype estimates", "seqkit_sample": "Sample sequences from FASTA/FASTQ files by number or proportion", "bam_tumor_normal_somatic_variant_calling_gatk": "Perform variant calling on a paired tumor normal set of samples using mutect2 tumor normal mode.\nf1r2 output o"}}, "target": "glimpse_sample", "target_idx": 2}
{"id": "mod_mcstaging_imc2mc_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Staging module for MCMICRO transforming Imaging Mass Cytometry .txt files to .tif files with OME-XML metadata. Includes optional hot pixel removal. (tools: mcstaging)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mcstaging/imc2mc": "Staging module for MCMICRO transforming Imaging Mass Cytometry .txt files to .tif files with OME-XML metadata.", "rclone/checksum": "Check files in a destination path against a checksum SUM file", "bftools/showinf": "Extract OME xml data from OME-tif", "taxonkit/lineage": "Convert taxonids to taxon lineages", "deepcell/mesmer": "Deepcell/mesmer segmentation for whole-cell"}}, "target": "mcstaging/imc2mc", "target_idx": 0}
{"id": "local_subworkflow_preparereports_2_5", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPAREREPORTS", "modules": ["custom/preparereports", "multiqc"], "description": "Custom aggregation and MultiQC reporting"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for PREPAREREPORTS (custom/preparereports, multiqc).", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow PREPAREREPORTS": null, "Use nf-core subworkflow preparereports": null, "Leave them out": null}}, "target": "Local subworkflow PREPAREREPORTS", "target_idx": 1}
{"id": "samplesheet_arch_cancer_tumor_only_0_4", "category": "samplesheet_schema", "state": {"technology": "Cancer Genomics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end FASTQ reads from tumor biopsy without matched normal"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Tumor-only somatic variant calling without matched normal?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 2}
{"id": "samplesheet_arch_ont_metagenome_single_0_0", "category": "samplesheet_schema", "state": {"assay": "Long-read Oxford Nanopore environmental metagenomic sequencing", "first_step": "NANOPLOT", "inputs": "High molecular weight environmental metagenomic long reads per sampling site", "pipeline": "nf-core/mag"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Long-read Oxford Nanopore environmental metagenomic sequencing?", "criteria": {"sample,fastq_1,group": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,fastq_1,group", "target_idx": 0}
{"id": "mod_gatk4_collectsvevidence_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Gathers paired-end and split read evidence files for use in the GATK-SV pipeline. Output files are a file containing the location of and orientation of read pairs marked as discordant, and a file containing the clipping location of all soft clipped reads and the orientation of the clipping. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abritamr/run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes", "gatk4/asereadcounter": "Calculates the allele-specific read counts for allele-specific expression analysis of RNAseq data", "gatk4/collectsvevidence": "Gathers paired-end and split read evidence files for use in the GATK-SV pipeline. Output files are a file cont", "gatk4/annotateintervals": "Annotates intervals with GC content, mappability, and segmental-duplication content", "mmseqs/databases": "Download an mmseqs-formatted database"}}, "target": "gatk4/collectsvevidence", "target_idx": 2}
{"id": "resource_blast_makeblastdb_5", "category": "resource_profiling", "state": {"process": "BLAST_MAKEBLASTDB", "tool": "blast/makeblastdb", "description": "Builds a BLAST database"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLAST_MAKEBLASTDB (Builds a BLAST database) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_krona_kronadb_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: KronaTools Update Taxonomy downloads a taxonomy database (tools: krona)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/spaddintrons": null, "bakta/baktadbdownload": null, "blast/blastdbcmd": null, "fairy/coverage": null, "krona/kronadb": null}}, "target": "krona/kronadb", "target_idx": 4}
{"id": "qc_adapt_singlecell_multiqc_2_11", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample single-cell RNA-seq cohort (summary_reporting).", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "mod_openms_textexporter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Exports various OpenMS XML formats (featureXML, consensusXML, idXML, mzML) to a human-readable text format. (tools: openms)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hhsuite_hhblits": "Fast and sensitive protein sequence searching based on the pairwise alignment of hidden Markov models (HMMs)", "cnvkit_export": "Convert copy number ratio tables (.cnr files) or segments (.cns) to another format.", "unzipfiles": "Unzip ZIP archive files", "openms_textexporter": "Exports various OpenMS XML formats (featureXML, consensusXML, idXML, mzML) to a human-readable text format.", "openms_idfilter": "Filters peptide/protein identification results by different criteria."}}, "target": "openms_textexporter", "target_idx": 3}
{"id": "subworkflow_pkg_bam_rseqc_3", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_RSEQC", "modules": ["rseqc", "rseqc/tin", "rseqc/readduplication", "rseqc/readdistribution", "rseqc/junctionsaturation", "rseqc/junctionannotation", "rseqc/innerdistance", "rseqc/inferexperiment", "rseqc/bamstat"], "description": "Subworkflow to run multiple commands in the RSeqC package"}, "question": {"type": "choice", "instructions": "How should BAM_RSEQC (rseqc, rseqc/tin, rseqc/readduplication, rseqc/readdistribution, rseqc/junctionsaturation, rseqc/junctionannotation, rseqc/innerdistance, rseqc/inferexperiment, rseqc/bamstat) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow bam_rseqc": null, "Local subworkflow BAM_RSEQC": null}}, "target": "Use nf-core subworkflow bam_rseqc", "target_idx": 2}
{"id": "mod_orthofinder_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: OrthoFinder is a fast, accurate and comprehensive platform for comparative genomics. (tools: orthofinder)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"orthofinder": "OrthoFinder is a fast, accurate and comprehensive platform for comparative genomics.", "agat_spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated", "seqkit_fq2fa": "Convert FASTQ to FASTA format", "agat_spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "picard_setnmmdanduqtags": "This tool takes in a coordinate-sorted SAM or BAM and calculatesthe NM, MD, and UQ tags by comparing with the "}}, "target": "orthofinder", "target_idx": 0}
{"id": "pipe_all101_pacvar_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Longread PacBio sequencing processing for WGS and PureTarget. Topics: alignment, long-read, pacbio, puretarget, variant-calling, wgs. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"rnasplice": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis [alternative-splicing, rna, rna-seq]", "kmermaid": " k-mer similarity analysis pipeline [k-mer, kmer, kmer-counting]", "molkart": "A pipeline for processing Molecular Cartography data from Resolve Bioscience (combinatorial FISH) [fish, image-processin", "funcprofiler": "Read-based functional profiling of microbiome sequencing data", "pacvar": "Longread PacBio sequencing processing for WGS and PureTarget [alignment, long-read, pacbio]"}}, "target": "pacvar", "target_idx": 4}
{"id": "samplesheet_arch_cancer_somatic_bam_4_2", "category": "samplesheet_schema", "state": {"assay": "Somatic tumor-normal calling from pre-aligned BAM files", "first_step": "MUTECT2"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Coordinate-sorted BAMs with index for tumor and normal samples?", "criteria": {"patient,sample,bam": null, "patient,sample,status,bam,bai": null, "sample,vcf": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 1}
{"id": "mod_fastq_remove_rrna_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Remove ribosomal RNA reads from FASTQ files using SortMeRNA, RiboDetector, or Bowtie2 (tools: fastq_remove_rrna)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamtofastq10x": "Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ATAC, Cell Ranger DNA, and Lon", "adapterremovalfixprefix": "Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with", "fastq_remove_rrna": "Remove ribosomal RNA reads from FASTQ files using SortMeRNA, RiboDetector, or Bowtie2", "cellpose": "cellpose segments cells in images using GPU-accelerated deep learning", "quantify_pseudo_alignment": "Perform quantification with Salmon or Kallisto to produce count tables and SummarizedExperiment objects"}}, "target": "fastq_remove_rrna", "target_idx": 2}
{"id": "subworkflow_pkg_fastq_preprocess_seqkit_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_PREPROCESS_SEQKIT", "modules": ["fastq_sanitise_seqkit", "seqkit/sana", "seqkit/pair", "seqkit/seq", "seqkit/replace", "seqkit/rmdup"], "description": "Subworkflow that preprocesses FASTQ files"}, "question": {"type": "choice", "instructions": "How should FASTQ_PREPROCESS_SEQKIT (fastq_sanitise_seqkit, seqkit/sana, seqkit/pair, seqkit/seq, seqkit/replace, seqkit/rmdup) be structured in DSL2?", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow FASTQ_PREPROCESS_SEQKIT": null, "Use nf-core subworkflow fastq_preprocess_seqkit": null}}, "target": "Use nf-core subworkflow fastq_preprocess_seqkit", "target_idx": 3}
{"id": "samplesheet_arch_methylseq_bisulfite_3_2", "category": "samplesheet_schema", "state": {"technology": "Epigenomics", "workflow_entry": "FASTQC", "library_inputs": "Bisulfite-converted or enzymatic methyl-converted paired-end FASTQs"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Whole-Genome Bisulfite Sequencing (WGBS / EM-seq) with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,cpg,methylation": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "intent_prepare_data_20", "category": "intent_routing", "state": "Classify this user request: \"Generate a script to parse our SRA run table and stage paired-end FASTQ downloads for Nextflow.\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes"}}, "target": "prepare_data", "target_idx": 3}
{"id": "resource_bedtools_genomecov_0", "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_high": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_cfdna_liquid_biopsy_2_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 should the input samplesheet have?", "criteria": {"sample,timepoint,fastq": null, "patient,sample,timepoint,volume_ml,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,volume_ml,fastq_1,fastq_2", "target_idx": 1}
{"id": "pipe_all101_chipseq_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: 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": {"chipseq": null, "proteinannotator": null, "proteogenomicsdb": null, "methylseq": null, "cutandrun": null}}, "target": "chipseq", "target_idx": 0}
{"id": "subworkflow_pkg_bam_stats_mirna_mirtop_0", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_STATS_MIRNA_MIRTOP", "modules": ["mirtop/gff", "mirtop/counts", "mirtop/export", "mirtop/stats"], "description": "mirtop is a command line tool to annotate miRNAs and isomiRs and compute general statistics using the mirGFF3 format."}, "question": {"type": "choice", "instructions": "How should BAM_STATS_MIRNA_MIRTOP (mirtop/gff, mirtop/counts, mirtop/export, mirtop/stats) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow BAM_STATS_MIRNA_MIRTOP": null, "Use nf-core subworkflow bam_stats_mirna_mirtop": null}}, "target": "Use nf-core subworkflow bam_stats_mirna_mirtop", "target_idx": 3}
{"id": "samplesheet_arch_ancient_dna_eager_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/eager", "assay_type": "Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment", "data_format": "Ancient degraded DNA FASTQs with library preparation chemistry and uracil-DNA-glycosylase status"}, "question": {"type": "choice", "instructions": "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,fastq_1,fastq_2": null, "sample,bam": null, "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 2}
{"id": "field_constraint_bam_0_6", "category": "samplesheet_schema", "state": {"field_name": "bam", "datatype": "file_pattern", "description": "Path to aligned binary sequence alignment (BAM) file"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'bam'?", "criteria": {"pattern: ^\\S+\\.vcf(\\.gz)?$": null, "format: uri": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 3}
{"id": "mod_fasta_gtf_bam_rpbp_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: End-to-end translated-ORF discovery from ribosome profiling (Ribo-seq) data\nwith Rp-Bp (Malone et al. 2017). Ribo-seq sequences the short mRNA\nfootprints protected by translating ribosomes; Rp-Bp uses a Bayesian model\nto score which open reading frames (ORFs) on the transcriptome show the\ncharacteristic 3-nucleotide periodicity of active translation.\n\nGiven a genome FASTA, annotation GTF and one or more pre-aligned Ribo-seq\nBAMs, the subworkflow:\n  1. Builds the per-ORF reference (rpbp/preparegenome) once per run -\n     enumerates candidate ORFs from the GTF.\n  2. For each sample, builds per-read-length metagene profiles around\n     annotated start codons (extract-metagene-profiles), scores their\n     three-nucleotide periodicity with Bayesian models\n     (estimate-metagene-profile-bayes-factors), picks the best P-site\n     offset per periodic read length (select-periodic-offsets), and\n     filters down to the high-confidence read-length/offset pairs that\n     will drive ORF-level scoring (get-periodic-lengths-offsets).\n  3. Builds per-ORF P-site count vectors with those selected offsets\n     (extract-orf-profiles), scores each ORF as \"translated\" vs\n     \"untranslated\" with a Bayesian model (estimate-orf-bayes-factors),\n     and emits the final filtered set of predicted translated ORFs as\n     BED + DNA FASTA + protein FASTA (select-final-prediction-set).\n\nEach Rp-Bp step is a separate Nextflow process so `-resume` only re-runs\nwhat changed, and STAR/bowtie alignment is supplied via the BAM input\n(this subworkflow does not realign). (tools: fasta_gtf_bam_rpbp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amrfinderplus/run": "Identify antimicrobial resistance in gene or protein sequences", "rpbp/preparegenome": "Build the per-ORF reference files that Rp-Bp's downstream scoring needs,\nstarting from a genome FASTA and an a", "fasta_gtf_bam_rpbp": "End-to-end translated-ORF discovery from ribosome profiling (Ribo-seq) data\nwith Rp-Bp (Malone et al. 2017). R", "rpbp/extractorfprofiles": "Build a per-ORF P-site count vector for every candidate open reading\nframe (ORF) in the catalogue. For each OR", "pdb2pqr": "Convert PDB files to PQR format by\nassigning charge and radius parameters for\nelectrostatics calculations (e.g"}}, "target": "fasta_gtf_bam_rpbp", "target_idx": 2}
{"id": "subworkflow_pkg_fasta_build_add_kraken2_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_BUILD_ADD_KRAKEN2", "modules": ["kraken2/add", "kraken2/build"], "description": "KRAKEN2 build custom database subworkflow"}, "question": {"type": "choice", "instructions": "How should FASTA_BUILD_ADD_KRAKEN2 (kraken2/add, kraken2/build) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow FASTA_BUILD_ADD_KRAKEN2": null, "Leave them out": null, "Use nf-core subworkflow fasta_build_add_kraken2": null}}, "target": "Use nf-core subworkflow fasta_build_add_kraken2", "target_idx": 3}
{"id": "noul_subworkflow_structural_blocks_0", "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_singlecell_parse_splitseq_5_4", "category": "samplesheet_schema", "state": {"assay": "Parse Biosciences Split-seq combinatorial barcoding", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/scrnaseq, determine the input samplesheet column structure for: Parse Biosciences Split-seq combinatorial barcoding.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,subpool,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,subpool,fastq_1,fastq_2", "target_idx": 2}
{"id": "resource_blobtk_snail_2", "category": "resource_profiling", "state": {"process": "BLOBTK_SNAIL", "tool": "blobtk/snail", "description": "Creates blobtk snail plots."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLOBTK_SNAIL (Creates blobtk snail plots.) in conf/base.config?", "criteria": {"process_high": null, "process_low": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "subworkflow_pkg_fastq_shortreads_preprocess_qc_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_SHORTREADS_PREPROCESS_QC", "modules": ["fastq_qc_stats", "fastqc", "seqfu/check", "seqfu/stats", "seqkit/stats", "seqtk/comp", "fastq_preprocess_seqkit", "fastq_sanitise_seqkit", "seqkit/sana", "seqkit/pair", "seqkit/seq", "seqkit/replace", "seqkit/rmdup", "umitools/extract", "fastq_removeadapters_merge", "trimmomatic", "cutadapt", "trimgalore", "bbmap/bbduk", "leehom", "fastp", "adapterremoval", "cat/fastq", "fastq_complexity_filter", "prinseqplusplus", "bbmap/clumpify", "fastq_decontaminate_deacon_hostile", "fastq_index_filter_deacon", "fastq_fetch_clean_hostile", "hostile/fetch", "hostile/clean", "bowtie2/build", "deacon/filter", "deacon/index"], "description": "Quality check and preprocessing subworkflow of Illumina short reads"}, "question": {"type": "choice", "instructions": "How should FASTQ_SHORTREADS_PREPROCESS_QC (fastq_qc_stats, fastqc, seqfu/check, seqfu/stats, seqkit/stats, seqtk/comp, fastq_preprocess_seqkit, fastq_sanitise_seqkit, seqkit/sana, seqkit/pair, seqkit/seq, seqkit/replace, seqkit/rmdup, umitools/extract, fastq_removeadapters_merge, trimmomatic, cutadapt, trimgalore, bbmap/bbduk, leehom, fastp, adapterremoval, cat/fastq, fastq_complexity_filter, prinseqplusplus, bbmap/clumpify, fastq_decontaminate_deacon_hostile, fastq_index_filter_deacon, fastq_fetch_clean_hostile, hostile/fetch, hostile/clean, bowtie2/build, deacon/filter, deacon/index) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow FASTQ_SHORTREADS_PREPROCESS_QC": null, "Use nf-core subworkflow fastq_shortreads_preprocess_qc": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fastq_shortreads_preprocess_qc", "target_idx": 2}
{"id": "qc_adapt_illumina_novaseq_1_33", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "resource_bbmap_pileup_0", "category": "resource_profiling", "state": {"process": "BBMAP_PILEUP", "tool": "bbmap/pileup", "description": "Calculates per-scaffold or per-base coverage information from an unsorted sam or bam file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_PILEUP (Calculates per-scaffold or per-base coverage information from an unsorted sam or) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_arcashla_extract_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extracts reads mapped to chromosome 6 and any HLA decoys or chromosome 6 alternates. (tools: arcashla)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_pluginsetgt": "Sets genotypes according to the specified criteria and filtering expressions. For example, missing genotypes c", "hlala_preparegraph": "Pre-compute the graph index structure.", "comebin_runcomebin": "Effective binning of metagenomic contigs using COntrastive Multi-viEw representation learning", "magus_align": "Multiple Sequence Alignment using Graph Clustering", "arcashla_extract": "Extracts reads mapped to chromosome 6 and any HLA decoys or chromosome 6 alternates."}}, "target": "arcashla_extract", "target_idx": 4}
{"id": "resource_blast_updateblastdb_1", "category": "resource_profiling", "state": {"process": "BLAST_UPDATEBLASTDB", "tool": "blast/updateblastdb", "description": "Downloads a BLAST database from NCBI"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLAST_UPDATEBLASTDB (Downloads a BLAST database from NCBI) in conf/base.config?", "criteria": {"process_low": null, "process_medium": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "qc_adapt_bulk_multiqc_0_11", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For High-throughput bulk WGS multi-sample run, what is the recommended QC default for MultiQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "samplesheet_arch_ont_metagenome_single_7_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/mag", "assay_type": "Long-read Oxford Nanopore environmental metagenomic sequencing", "data_format": "High molecular weight environmental metagenomic long reads per sampling site"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for single-end ONT?", "criteria": {"sample,fastq_1,group": null, "sample,fastq_1": null, "sample,bam": null, "sample,fasta": null}}, "target": "sample,fastq_1,group", "target_idx": 0}
{"id": "resource_annotsv_installannotations_4", "category": "resource_profiling", "state": {"process": "ANNOTSV_INSTALLANNOTATIONS", "tool": "annotsv/installannotations", "description": "Install the AnnotSV annotations"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANNOTSV_INSTALLANNOTATIONS (Install the AnnotSV annotations) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_pe_illumina_fastqc_0_38", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_vcf_extract_relate_somalier_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform somalier extraction and relate stats on input VCFs (tools: vcf_extract_relate_somalier)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ltrretriever/lai": "Estimates the mean LTR sequence identity in the genome. The input genome fasta should\nhave short alphanumeric ", "bamtools/stats": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "vcf_extract_relate_somalier": "Perform somalier extraction and relate stats on input VCFs", "bamutil/trimbam": "trims the end of reads in a SAM/BAM file, changing read ends to ‘N’ and quality to ‘!’, or by soft clipping", "vcflib/vcffixup": "Generates a VCF stream where AC and NS have been generated for each record using sample genotypes."}}, "target": "vcf_extract_relate_somalier", "target_idx": 2}
{"id": "intent_ask_question_7", "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, "debug_error": null, "ask_question": null, "build_pipeline": null}}, "target": "ask_question", "target_idx": 2}
{"id": "qc_adapt_singlecell_multiqc_2_49", "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": "qc_adapt_singlecell_multiqc_2_44", "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": "resource_bamtools_stats_3", "category": "resource_profiling", "state": {"process": "BAMTOOLS_STATS", "tool": "bamtools/stats", "description": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMTOOLS_STATS (BamTools provides both a programmer's API and an end-user's toolkit for handling) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_pacbio_hifi_2_45", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "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_cancer_somatic_bam_1_5", "category": "samplesheet_schema", "state": {"assay": "Somatic tumor-normal calling from pre-aligned BAM files", "first_step": "MUTECT2", "template": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Somatic tumor-normal calling from pre-aligned BAM files?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,bam,bai": null, "patient,sample,status,bam,bai": null, "patient,sample,bam": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 2}
{"id": "mod_custom_summarisetelomereestimation_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Normalise and combine telomere length and content estimates from telseq, telogator2, and telomerehunter into a unified summary (tools: pandas)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom_summarisetelomereestimation": "Normalise and combine telomere length and content estimates from telseq, telogator2, and telomerehunter into a", "sentieon_collectvcmetrics": "Accelerated implementation of the Picard CollectVariantCallingMetrics tool.", "telogator2": "Allele-specific telomere length estimation and TVR characterization from long reads", "tidk_search": "Searches a genome for a telomere string such as TTAGGG", "amulety_esm2": "A module to create esm2 embeddings of antibody (BCR) amino acid sequences using amulety."}}, "target": "custom_summarisetelomereestimation", "target_idx": 0}
{"id": "qc_adapt_qc_aggregate_2_48", "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_1_1_3", "category": "samplesheet_schema", "state": {"column": "fastq_1", "purpose": "Path to read 1 FASTQ file (gzipped or uncompressed)"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'fastq_1' (Path to read 1 FASTQ file (gzipped or uncompressed)).", "criteria": {"type: integer": null, "pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "enum: [auto, forward, reverse, unstranded]": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 2}
{"id": "noul_channel_join_operator_20", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.join()` operator combines two channels sharing a matching key (like `meta.id`).\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_pairtools_sort_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sort a .pairs/.pairsam file (tools: pairtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"prodigal": "Prodigal (Prokaryotic Dynamic Programming Genefinding Algorithm) is a microbial (bacterial and archaeal) gene ", "survivor_stats": "Report multiple stats over a VCF file", "pairtools_sort": "Sort a .pairs/.pairsam file", "csvtk_sort": "Sort  CSV (or TSV) tables", "bedtools_sort": "Sorts a feature file by chromosome and other criteria."}}, "target": "pairtools_sort", "target_idx": 2}
{"id": "pipe_all101_smrnaseq_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for small-rna. 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]", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline [adna, ancient-dna-analysis, ancientdna]", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "funcscan": "(Meta-)genome screening for functional and natural product gene sequences [amp, amr, antibiotic-resistance]", "crisprseq": "A pipeline for the analysis of CRISPR edited data. It allows the evaluation of the quality of gene editing experiments u", "methylseq": "Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair [bisulfi", "detaxizer": "A pipeline to identify (and remove) certain sequences from raw genomic data. Default taxon to identify (and remove) is H", "ribomsqc": "QC pipeline that monitors mass spectrometer performance in ribonucleoside analysis", "spatialaxe": "A bioinformatics best-practice processing and quality control pipeline for Xenium and Artera data [10x-genomics, atera, ", "smrnaseq": "A small-RNA sequencing analysis pipeline [small-rna, smrna-seq]"}}, "target": "smrnaseq", "target_idx": 9}
{"id": "noul_named_output_channel_access_3", "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_bbmap_repair_2", "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_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_umitools_extract_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extracts UMI barcode from a read and add it to the read name, leaving any sample barcode in place (tools: umi_tools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"umitools/extract": null, "chelae/trim": null, "staphopiasccmec": null, "fgbio/callduplexconsensusreads": null, "ucsc/bedgraphtobigwig": null}}, "target": "umitools/extract", "target_idx": 0}
{"id": "mod_picard_positionbaseddownsamplesam_1", "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": {"picard_positionbaseddownsamplesam": "Samples a SAM/BAM/CRAM file using flowcell position information for the best approximation of having sequenced", "seqtk_sample": "Subsample reads from FASTQ files", "bcftools_csq": "bcftools Haplotype-aware consequence caller", "glimpse_phase": "main GLIMPSE algorithm, performs phasing and imputation refining genotype likelihoods", "glimpse_sample": "Generates haplotype calls by sampling haplotype estimates"}}, "target": "picard_positionbaseddownsamplesam", "target_idx": 0}
{"id": "intent_debug_error_17", "category": "intent_routing", "state": "Classify this user request: \"ERROR ~ Error executing process > 'SAMTOOLS_SORT' (command not found, exit status 127)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": null, "build_pipeline": null, "ask_question": null, "debug_error": null}}, "target": "debug_error", "target_idx": 3}
{"id": "core_tool_spades_metaspades_bare_2", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? De novo assembler specifically optimized for complex microbial metagenomic mixtures, recovering contigs across unequal coverage depths.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"spades_metaspades": null, "megahit": null, "unicycler": null, "flye": null, "canu": null}}, "target": "spades_metaspades", "target_idx": 0}
{"id": "qc_adapt_qc_aggregate_0_25", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "For Multi-sample QC aggregation and reporting, what is the recommended QC default for MultiQC?", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "resource_bcftools_pluginimputeinfo_5", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINIMPUTEINFO", "tool": "bcftools/pluginimputeinfo", "description": "Adds imputation information metrics to the INFO field based on selected FORMAT tags. Only the IMPUTE2 INFO metric from FORMAT/GP tags is currently available."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINIMPUTEINFO (Adds imputation information metrics to the INFO field based on selected FORMAT t) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_metagenome_mag_grouped_5_3", "category": "samplesheet_schema", "state": {"assay": "Metagenomic MAG assembly with comparative groups", "first_step": "FASTQC", "inputs": "Paired-end environmental metagenomic FASTQs annotated by environmental cohort/group"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/mag, determine the input samplesheet column structure for: Metagenomic MAG assembly with comparative groups.", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null, "sample,fasta": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,group", "target_idx": 1}
{"id": "samplesheet_arch_cancer_somatic_tn_1_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Somatic cancer variant calling with tumor-normal pairs)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Somatic cancer variant calling with tumor-normal pairs?", "criteria": {"sample,fastq_1,fastq_2": null, "patient,sample,status,bam,bai": null, "sample,fastq_1": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 3}
{"id": "samplesheet_arch_ont_metagenome_single_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/mag) for Long-read Oxford Nanopore environmental metagenomic sequencing. Input files: High molecular weight environmental metagenomic long reads per sampling site.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Long-read Oxford Nanopore environmental metagenomic sequencing?", "criteria": {"sample,fastq_1,fastq_2,group": null, "sample,bam": null, "sample,fasta": null, "sample,fastq_1,group": null}}, "target": "sample,fastq_1,group", "target_idx": 3}
{"id": "samplesheet_arch_scrna_multiome_5_2", "category": "samplesheet_schema", "state": {"assay": "10x Multiome single-cell joint RNA and ATAC chromatin", "first_step": "FASTQC", "inputs": "Paired FASTQs for both GEX and ATAC modalities per nucleus", "pipeline": "nf-core/scrnaseq"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/scrnaseq, determine the input samplesheet column structure for: 10x Multiome single-cell joint RNA and ATAC chromatin.", "criteria": {"sample,rna_fastq,atac_fastq": null, "sample,fastq_1,fastq_2,feature_type": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 1}
{"id": "mod_angsd_docounts_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculates base frequency statistics across reference positions from BAM. (tools: angsd)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"somalier_relate": null, "angsd_docounts": null, "angsd_gl": null, "pigz_uncompress": null, "bam_docounts_contamination_angsd": null}}, "target": "angsd_docounts", "target_idx": 1}
{"id": "mod_fastplong_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform adapter/quality trimming and QC on long sequencing reads (ONT, PacBio, etc.) (tools: fastplong)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastplong": null, "chromap/chromap": null, "openms/peptideindexer": null, "chopper": null, "iphop/download": null}}, "target": "fastplong", "target_idx": 0}
{"id": "mod_ariba_run_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Query input FASTQs against Ariba formatted databases (tools: ariba)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ariba/run": "Query input FASTQs against Ariba formatted databases", "hamronization/abricate": "Tool to convert and summarize ABRicate outputs using the hAMRonization specification", "cellrangerarc/mkref": "Module to build the reference needed by the 10x Genomics Cell Ranger Arc tool. Uses the cellranger-arc mkref c", "adapterremovalfixprefix": "Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with", "bamtools/convert": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files."}}, "target": "ariba/run", "target_idx": 0}
{"id": "resource_bamtools_stats_0", "category": "resource_profiling", "state": {"process": "BAMTOOLS_STATS", "tool": "bamtools/stats", "description": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMTOOLS_STATS (BamTools provides both a programmer's API and an end-user's toolkit for handling) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_bulk_rnaseq_se_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/rnaseq) for Single-end Illumina RNA-seq with strandedness. Input files: Single-end FASTQ reads per library.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Single-end Illumina RNA-seq with strandedness?", "criteria": {"sample,bam": null, "sample,vcf": null, "sample,fastq_1,strandedness": null, "sample,fastq_1,fastq_2,strandedness": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 2}
{"id": "mod_scimap_spatiallda_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: SpatialLDA uses an LDA based approach for the identification of cellular neighborhoods, using cell type identities. (tools: scimap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abricate_summary": "Screen assemblies for antimicrobial resistance against multiple databases", "scimap_spatiallda": "SpatialLDA uses an LDA based approach for the identification of cellular neighborhoods, using cell type identi", "custom_bed12codonpositions": "Expand a BED12 into a BED6 of in-frame mRNA positions, projected back\nto genomic coordinates. Default behaviou", "seacr_callpeak": "Call peaks using SEACR on sequenced reads in bedgraph format", "deepcell_mesmer": "Deepcell/mesmer segmentation for whole-cell"}}, "target": "scimap_spatiallda", "target_idx": 1}
{"id": "qc_adapt_ffpe_wes_2_38", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_propr_grea_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform Gene Ratio Enrichment Analysis (tools: grea)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"propr_logratio": "Transform the data matrix using centered logratio transformation (CLR) or additive logratio transformation (AL", "propr_propr": "Perform logratio-based correlation analysis -> get proportionality & basis shrinkage partial correlation coeff", "hifitrimmer_trim": "Run hifi-trimmer trim to filter and trim adapter-hit regions from PacBio HiFi reads.\nSupports BAM/CRAM/FASTA/F", "msisensorpro_scan": "MSIsensor-pro evaluates Microsatellite Instability (MSI) for cancer patients with next generation sequencing d", "propr_grea": "Perform Gene Ratio Enrichment Analysis"}}, "target": "propr_grea", "target_idx": 4}
{"id": "mod_pigz_uncompress_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: write your description here (tools: pigz)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ucsc_gtftogenepred": null, "rmarkdownnotebook": null, "crabz_decompress": null, "crabz_compress": null, "pigz_uncompress": null}}, "target": "pigz_uncompress", "target_idx": 4}
{"id": "resource_bamclipper_0", "category": "resource_profiling", "state": {"process": "BAMCLIPPER", "tool": "bamclipper", "description": "This module is used to clip primer sequences from your alignments."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMCLIPPER (This module is used to clip primer sequences from your alignments.) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_prealigned_cram_indexed_3_1", "category": "samplesheet_schema", "state": {"assay": "Genome analysis from reference-compressed CRAM files", "first_step": "GATK_HAPLOTYPECALLER", "template": "nf-core/sarek"}, "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,crai": null, "sample,fastq_1,fastq_2": null, "sample,bam,bai": null, "sample,vcf": null}}, "target": "sample,cram,crai", "target_idx": 0}
{"id": "mod_bedtools_nuc_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Profiles the nucleotide content of intervals in a fasta file. (tools: bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bedops_convert2bed": "Convert BAM/GFF/GTF/GVF/PSL files to bed", "agat_convertbed2gff": "Takes a bed12 file and converts to a GFF3 file", "vrhyme_extractunbinned": "Extracting sequences that were unbinnned by vRhyme into a FASTA file", "gt_ltrharvest": "Predicts LTR retrotransposons using GenomeTools gt-ltrharvest utility", "bedtools_nuc": "Profiles the nucleotide content of intervals in a fasta file."}}, "target": "bedtools_nuc", "target_idx": 4}
{"id": "mod_vizgenpostprocessing_preparesegmentation_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The module prepares the specification JSON file for Vizgen's post-processing tool\ncell segmentation workflow. (tools: vizgenpostprocessing)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"coreograph": "Great....yet another TMA dearray program. What does this one do? Coreograph uses UNet, a deep learning model, ", "umicollapse": "Deduplicate reads based on the mapping co-ordinate and the UMI attached to the read.", "vizgenpostprocessing/preparesegmentation": "The module prepares the specification JSON file for Vizgen's post-processing tool\ncell segmentation workflow.", "baysor/run": "Bayesian segmentation of spatial transcriptomics data.", "wgsim": "simulating sequence reads from a reference genome"}}, "target": "vizgenpostprocessing/preparesegmentation", "target_idx": 2}
{"id": "qc_adapt_bulk_multiqc_1_13", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep FastQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "samplesheet_arch_cutandrun_pe_7_1", "category": "samplesheet_schema", "state": {"assay": "CUT&RUN / CUT&TAG chromatin profiling with IgG control", "first_step": "FASTQC", "template": "nf-core/cutandrun"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for ChIP-seq with controls?", "criteria": {"sample,target,control": null, "sample,fastq_1,fastq_2,target,control": null, "sample,spikein,fastq": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 1}
{"id": "samplesheet_arch_chipseq_with_control_7_0", "category": "samplesheet_schema", "state": {"assay": "ChIP-seq with IP and input control design", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for ChIP-seq with controls?", "criteria": {"sample,antibody,control": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,antibody,control": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 2}
{"id": "mod_variantbam_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filtering, downsampling and profiling alignments in BAM/CRAM formats (tools: variantbam)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamcmp": "Bamcmp (Bam Compare) is a tool for assigning reads between a primary genome and a contamination genome. For in", "agat/spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "variantbam": "Filtering, downsampling and profiling alignments in BAM/CRAM formats", "gecco/run": "GECCO is a fast and scalable method for identifying putative novel Biosynthetic Gene Clusters (BGCs) in genomi", "meryl/unionsum": "A genomic k-mer counter (and sequence utility) with nice features."}}, "target": "variantbam", "target_idx": 2}
{"id": "schema_std_pixelator_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/pixelator", "description": "Pipeline to generate Proximity Network Assay data with Pixelator (Pixelgen Technologies AB)", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/pixelator?", "criteria": {"ID,Sample,Condition,ReplicateFileName,Fasta": null, "sample,fastq_1,fastq_2,pool,hash_index": null, "ID,R1,R2,LongFastQ,Fast5": null, "sample,type,level,msfile": null}}, "target": "sample,fastq_1,fastq_2,pool,hash_index", "target_idx": 1}
{"id": "samplesheet_arch_prealigned_bam_indexed_2_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 should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam,bai": null, "sample,vcf": null}}, "target": "sample,bam,bai", "target_idx": 2}
{"id": "mod_parabricks_fq2bam_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: NVIDIA Clara Parabricks GPU-accelerated alignment, sorting, BQSR calculation, and duplicate marking. Note this nf-core module requires files to be copied into the working directory and not symlinked. (tools: parabricks)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gzrt": "gzrecover is a program that will attempt to extract any readable data out of a gzip file that has been corrupt", "ampcombi2/complete": "A submodule that merges all output summary tables from ampcombi/parsetables in one summary file.", "refsolver/compare": "Compare two sequence dictionaries (headers/references) using ref-solver", "ampcombi": "A tool to parse and summarise results from antimicrobial peptides tools and present functional classification.", "parabricks/fq2bam": "NVIDIA Clara Parabricks GPU-accelerated alignment, sorting, BQSR calculation, and duplicate marking. Note this"}}, "target": "parabricks/fq2bam", "target_idx": 4}
{"id": "samplesheet_arch_pediatric_trio_somatic_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/sarek", "assay_type": "Pediatric cancer trio (Child Proband tumor, Proband germline, Parents)", "data_format": "Paired-end FASTQs tracking patient, sample, tissue status (normal/tumor), and maternal/paternal lineage"}, "question": {"type": "choice", "instructions": "Which columns are standard for Pediatric cancer trio (Child Proband tumor, Proband germline, Parents) input samplesheet?", "criteria": {"sample,bam,bai": null, "sample,fastq_1,fastq_2": null, "family_id,patient,sample,status,sex,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": 2}
{"id": "resource_blast_blastp_2", "category": "resource_profiling", "state": {"process": "BLAST_BLASTP", "tool": "blast/blastp", "description": "BLASTP (Basic Local Alignment Search Tool- Protein) compares an amino acid (protein) query sequence against a protein database"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLAST_BLASTP (BLASTP (Basic Local Alignment Search Tool- Protein) compares an amino acid (prot) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_minimac4_compressref_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compression of a reference panel for genotype imputation to `.msav` format (tools: minimac4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"eagle2": "Perform phasing of genotyped data with or without a reference panel", "minimac4_compressref": "Compression of a reference panel for genotype imputation to `.msav` format", "whatshap_haplotag": "Tag reads by haplotype", "whatshap_stats": "Compute statistics from phased variant file using Whatshap", "bedtools_flank": "Creates two new flanking intervals for each interval in a BED/GFF/VCF file."}}, "target": "minimac4_compressref", "target_idx": 1}
{"id": "samplesheet_arch_bulk_rnaseq_se_3_2", "category": "samplesheet_schema", "state": {"technology": "Bulk RNA-seq", "workflow_entry": "FASTQC", "library_inputs": "Single-end FASTQ reads per library"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Single-end Illumina RNA-seq with strandedness with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,strandedness": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 1}
{"id": "resource_bigslice_downloaddb_0", "category": "resource_profiling", "state": {"process": "BIGSLICE_DOWNLOADDB", "tool": "bigslice/downloaddb", "description": "Downloads and extracts the BiG-SLiCE HMM database (biosynthetic and sub Pfams)\nusing the bundled `download_bigslice_hmmdb` script shipped with BiG-SLiCE.\nThe resulting directory can be passed directly as the `hmmdb` input to the\n`BIGSLICE` module."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIGSLICE_DOWNLOADDB (Downloads and extracts the BiG-SLiCE HMM database (biosynthetic and sub Pfams)\nu) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_bcftools_rohviz_0", "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_single": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "noul_channel_operator_map_13", "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_vcf_annotation_pipeline_5_5", "category": "samplesheet_schema", "state": {"assay": "Downstream functional annotation of pre-called VCF files", "first_step": "ENSEMBLVEP", "template": "nf-core/raredisease"}, "question": {"type": "choice", "instructions": "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,bed": null, "sample,vcf": null, "sample,vcf,tbi": null}}, "target": "sample,vcf,tbi", "target_idx": 3}
{"id": "mod_lissero_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Serogrouping Listeria monocytogenes assemblies (tools: lissero)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"aria2": "CLI Download utility", "expansionhunter": "Estimate repeat sizes using NGS data", "lissero": "Serogrouping Listeria monocytogenes assemblies", "any2fasta": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input ", "abritamr/run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes"}}, "target": "lissero", "target_idx": 2}
{"id": "schema_std_raredisease_0_0", "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": {"vcf,fasta,genome,site,source": null, "sample,fastq,cell_count": null, "sample,fastq_1,fastq_2,bam,bai": null, "sample,id,data_path,fastq_dir,cytaimage": null}}, "target": "sample,fastq_1,fastq_2,bam,bai", "target_idx": 2}
{"id": "samplesheet_arch_bulk_small_rna_2_5", "category": "samplesheet_schema", "state": {"assay": "Small RNA / miRNA sequencing", "first_step": "FASTQC", "inputs": "Single-end 50bp miRNA reads with 3-prime adapter"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,mirna_id": null, "sample,bam": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "mod_odgi_unchop_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge unitigs into a single node preserving the node order. (tools: odgi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"picard/cleansam": "Cleans the provided BAM, soft-clipping beyond-end-of-reference alignments and setting MAPQ to 0 for unmapped r", "odgi/draw": "Draw previously-determined 2D layouts of the graph with diverse annotations.", "umitools/extract": "Extracts UMI barcode from a read and add it to the read name, leaving any sample barcode in place", "odgi/unchop": "Merge unitigs into a single node preserving the node order.", "odgi/stats": "Metrics describing a variation graph and its path relationship."}}, "target": "odgi/unchop", "target_idx": 3}
{"id": "mod_untar_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extract files from tar, tar.gz, tar.bz2, tar.xz archives (tools: untar)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/spextractsequences": "This script extracts sequences in fasta format according to features described\nin a gff file.", "picard/extractfingerprint": "Computes/Extracts the fingerprint genotype likelihoods from the supplied file. It is given as a list of PLs at", "untar": "Extract files from tar, tar.gz, tar.bz2, tar.xz archives", "stainwarpy/register": "Register H&E stained and Multiplexed tissue images using feature-based image registration", "lofreq/call": "Lofreq subcommand to call low frequency variants from alignments"}}, "target": "untar", "target_idx": 2}
{"id": "noul_module_metadata_propagation_16", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, modules must accept and pass sample metadata tuples `[ val(meta), path(reads) ]` through channels.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_pypgx_createinputvcf_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Call SNVs/indels from BAM files for all target genes. (tools: pypgx)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"delly/call": null, "cadd": null, "ssuissero": null, "fasta_explore_search_plot_tidk": null, "pypgx/createinputvcf": null}}, "target": "pypgx/createinputvcf", "target_idx": 4}
{"id": "mod_hmmcopy_generatemap_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perl script (generateMap.pl) generates the mappability of a genome given a certain size of reads, for input to hmmcopy mapcounter. Takes a very long time on large genomes, is not parallelised at all. (tools: hmmcopy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"utils_nextflow_pipeline": null, "hmmcopy/gccounter": null, "controlfreec/assesssignificance": null, "gem2/gemindexer": null, "hmmcopy/generatemap": null}}, "target": "hmmcopy/generatemap", "target_idx": 4}
{"id": "local_subworkflow_variantsofint_2_0", "category": "subworkflow_packaging", "state": {"subworkflow": "VARIANTSOFINT", "modules": ["custom/variantsofint"], "description": "Variant filtering and clinical annotation aggregation"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for VARIANTSOFINT (custom/variantsofint).", "criteria": {"Leave them out": null, "Local subworkflow VARIANTSOFINT": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow variantsofint": null}}, "target": "Local subworkflow VARIANTSOFINT", "target_idx": 1}
{"id": "qc_adapt_ont_ultra_long_2_6", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "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": "schema_std_datasync_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/datasync", "assay": "datasync pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/datasync (nf-core/datasync is a system operation pipeline that provide)?", "criteria": {"sample,condition,assay,peak_file,footprinting": null, "condition,type,microbiome_path,alleles,weights_path": null, "fastq_1,fastq_2,batch,amp_batches,seq_batches": null, "sample,input,output_path,checksum_md5,checksum_sha": null}}, "target": "sample,input,output_path,checksum_md5,checksum_sha", "target_idx": 3}
{"id": "mod_trycycler_cluster_0", "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": {"gatk4/composestrtablefile": "This tool looks for low-complexity STR sequences along the reference that are later used to estimate the Drags", "galah": "Cluster genome FASTA files by average nucleotide identity", "isoseq/cluster": "IsoSeq - Cluster - Cluster trimmed consensus sequences", "repeatmasker/rmouttogff3": "A utility script to assist to convert old RepeatMasker *.out files to version 3 gff files.", "trycycler/cluster": "Cluster contigs from multiple assemblies by similarity"}}, "target": "trycycler/cluster", "target_idx": 4}
{"id": "mod_methbat_profile_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Runs methbat profile command to create methylation profiles for regions of interest from CpG metrics. (tools: methbat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gapseq_medium": "Predict growth medium from a draft model and pathway predictions", "optitype": "Perform HLA-I typing of sequencing data", "bismark_methylationextractor": "Extracts methylation information for individual cytosines from alignments.", "bismark_report": "Collects bismark alignment reports", "methbat_profile": "Runs methbat profile command to create methylation profiles for regions of interest from CpG metrics."}}, "target": "methbat_profile", "target_idx": 4}
{"id": "qc_adapt_pe_illumina_fastqc_2_17", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Standard Paired-end Illumina RNA-seq (short_reads_150bp).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_purgedups_splitfa_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Split fasta file by 'N's to aid in self alignment for duplicate purging (tools: purgedups)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"falco": "Run falco on sequenced reads", "atlas/splitmerge": "split single end read groups by length and merge paired end reads", "csvtk/split": "Splits CSV/TSV into multiple files according to column values", "purgedups/splitfa": "Split fasta file by 'N's to aid in self alignment for duplicate purging", "lofreq/callparallel": "It predicts variants using multiple processors"}}, "target": "purgedups/splitfa", "target_idx": 3}
{"id": "schema_std_proteinfamilies_0_0", "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,fasta,existing_hmms_to_update,existing_msas_to_update": null, "sample,bam,vcf,rna_matrix,hto_matrix": null, "sample_id,img_directory,parameter_file": null, "sample,fastq_1,fastq_2,batch,condition": null}}, "target": "sample,fasta,existing_hmms_to_update,existing_msas_to_update", "target_idx": 0}
{"id": "resource_bcftools_roh_1", "category": "resource_profiling", "state": {"process": "BCFTOOLS_ROH", "tool": "bcftools/roh", "description": "A program for detecting runs of homo/autozygosity. Only bi-allelic sites are considered."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_ROH (A program for detecting runs of homo/autozygosity. Only bi-allelic sites are con) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "field_constraint_phenotype_2_7", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'phenotype' (Affection status in clinical trio / family analysis) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'phenotype' validated?", "criteria": {"enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null, "type: string free-text": null, "enum: [normal, tumor]": null, "format: file-path": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 0}
{"id": "samplesheet_arch_pacbio_hifi_wgs_1_3", "category": "samplesheet_schema", "state": {"assay": "Long-read Pacific Biosciences HiFi sequencing", "first_step": "HIFIADAPTERFILT", "inputs": "Single HiFi BAM or FastQ"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Long-read Pacific Biosciences HiFi sequencing?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2,group": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "local_subworkflow_nextclade_1_5", "category": "subworkflow_packaging", "state": {"subworkflow": "NEXTCLADE", "modules": ["nextclade/run"], "description": "Viral clade typing and QC"}, "question": {"type": "choice", "instructions": "How should this step (nextclade/run) be packaged: Viral clade typing and QC?", "criteria": {"Local subworkflow NEXTCLADE": null, "Use nf-core subworkflow nextclade": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Local subworkflow NEXTCLADE", "target_idx": 0}
{"id": "resource_bedtools_bamtobed_2", "category": "resource_profiling", "state": {"process": "BEDTOOLS_BAMTOBED", "tool": "bedtools/bamtobed", "description": "Converts a bam file to a bed12 file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_BAMTOBED (Converts a bam file to a bed12 file.) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_bulk_small_rna_1_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/smrnaseq --input samplesheet.csv (Assay: Small RNA / miRNA sequencing)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Small RNA / miRNA sequencing?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,vcf": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "mod_ariba_getref_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Download and prepare database for Ariba analysis (tools: ariba)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ariba/getref": null, "ska/fasta": null, "bamtools/convert": null, "art/illumina": null, "checkqc": null}}, "target": "ariba/getref", "target_idx": 0}
{"id": "mod_centrifuger_quantification_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Quantification (taxonomic profiling) of Centrifuger model (tools: centrifuger)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"centrifuger/quantification": "Quantification (taxonomic profiling) of Centrifuger model", "binette": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "galah": "Cluster genome FASTA files by average nucleotide identity", "peddy": "Manipulation, validation and exploration of pedigrees"}}, "target": "centrifuger/quantification", "target_idx": 0}
{"id": "resource_binette_5", "category": "resource_profiling", "state": {"process": "BINETTE", "tool": "binette", "description": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning tools."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BINETTE (A fast and accurate binning refinement tool to construct high quality MAGs from ) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "samplesheet_arch_cutandrun_pe_7_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": "Which columns should the samplesheet have for ChIP-seq with controls?", "criteria": {"sample,target,control": null, "sample,fastq_1,fastq_2,target,control": null, "sample,spikein,fastq": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 1}
{"id": "mod_fastani_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Alignment-free computation of Average Nucleotide Identity (ANI) (tools: fastani)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/convertspgff2tsv": "Converts a GFF/GTF file into a TSV file", "plastid/makewiggle": "Create wiggle or bedGraph files from alignment files after applying a read mapping rule (e.g. to map ribosome-", "agat/convertgff2bed": "Takes a GFF3 file and converts to a bed12 file", "shigapass": "ShigaPass is an in silico tool used to predict Shigella serotypes and to differentiate between Shigella, EIEC ", "fastani": "Alignment-free computation of Average Nucleotide Identity (ANI)"}}, "target": "fastani", "target_idx": 4}
{"id": "subworkflow_pkg_fastq_remove_rrna_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_REMOVE_RRNA", "modules": ["bowtie2/align", "bowtie2/build", "ribodetector", "samtools/fastq", "samtools/view", "seqkit/replace", "seqkit/stats", "sortmerna"], "description": "Remove ribosomal RNA reads from FASTQ files using SortMeRNA, RiboDetector, or Bowtie2"}, "question": {"type": "choice", "instructions": "How should FASTQ_REMOVE_RRNA (bowtie2/align, bowtie2/build, ribodetector, samtools/fastq, samtools/view, seqkit/replace, seqkit/stats, sortmerna) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow FASTQ_REMOVE_RRNA": null, "Use nf-core subworkflow fastq_remove_rrna": null, "Leave them out": null}}, "target": "Use nf-core subworkflow fastq_remove_rrna", "target_idx": 2}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_6_5", "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 are standard for Hybrid bacterial assembly combining short Illumina and long Nanopore reads input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2,long_fastq": null, "sample,fasta": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 2}
{"id": "noul_default_empty_channel_behavior_18", "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": "noul_deprecated_file_output_syntax_1", "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": "subworkflow_pkg_fasta_clean_fcs_2", "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": "mod_samtools_fastq_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts a SAM/BAM/CRAM file to FASTQ (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"controlfreec_assesssignificance": null, "ascat": null, "fastq_align_bowtie2": null, "samtools_fastq": null, "atlas_pmd": null}}, "target": "samtools_fastq", "target_idx": 3}
{"id": "mod_picard_collectalignmentsummarymetrics_1", "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": {"picard_collectalignmentsummarymetrics": "Collect metrics about the alignment summary of a paired-end library.", "gcta_makebksparse": "Create a sparse GRM from a dense GRM for downstream fastGWA analyses", "fgumi_duplexmetrics": "Collects a suite of metrics to QC duplex sequencing data", "fgumi_simplexmetrics": "Collects a suite of metrics to QC simplex (single-strand) UMI sequencing data", "plink_vcf": "Analyses variant calling files using plink"}}, "target": "picard_collectalignmentsummarymetrics", "target_idx": 0}
{"id": "subworkflow_pkg_vcf_annotate_snpeff_1", "category": "subworkflow_packaging", "state": {"subworkflow": "VCF_ANNOTATE_SNPEFF", "modules": ["snpeff", "snpeff/snpeff", "htslib/bgziptabix"], "description": "Perform annotation with snpEff and bgzip + tabix index the resulting VCF file"}, "question": {"type": "choice", "instructions": "How should VCF_ANNOTATE_SNPEFF (snpeff, snpeff/snpeff, htslib/bgziptabix) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow VCF_ANNOTATE_SNPEFF": null, "Use nf-core subworkflow vcf_annotate_snpeff": null, "Leave them out": null}}, "target": "Use nf-core subworkflow vcf_annotate_snpeff", "target_idx": 2}
{"id": "pipe_all101_fastquorum_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Pipeline to produce consensus reads using unique molecular indexes/barcodes (UMIs). Topics: consensus, umi, umis, unique-molecular-identifier. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"ribomsqc": "QC pipeline that monitors mass spectrometer performance in ribonucleoside analysis", "seqsubmit": "nf-core pipeline for data submission to ENA", "references": "nf-core/references is a bioinformatics pipeline that build references, for multiple use cases [genome, references, repro", "proteinfamilies": "Generation and updating of protein families [metagenomics, protein-families]", "pairgenomealign": "Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plo", "fastquorum": "Pipeline to produce consensus reads using unique molecular indexes/barcodes (UMIs) [consensus, umi, umis]", "methylseq": "Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair [bisulfi", "phaseimpute": "A bioinformatics pipeline to phase and impute genetic data [genomics, genotype, imputation]"}}, "target": "fastquorum", "target_idx": 5}
{"id": "mod_vcf_impute_minimac4_0", "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": {"mmseqs_fasta_cluster": "Subworkflow that generates a clustering TSV file from a set of amino acid sequence within a FASTA file.", "vcf_impute_minimac4": "Subworkflow to impute VCF files using MINIMAC4 software. The subworkflow\ntakes VCF files, phased reference pan", "aardvark/merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF.", "ultra/index": "uLTRA aligner - A wrapper around minimap2 to improve small exon detection - Index gtf file for reads alignment", "bcftools/annotate": "Add or remove annotations."}}, "target": "vcf_impute_minimac4", "target_idx": 1}
{"id": "local_subworkflow_irma_1_2", "category": "subworkflow_packaging", "state": {"subworkflow": "IRMA", "modules": ["irma"], "description": "Iterative assembly step for influenza and coronavirus"}, "question": {"type": "choice", "instructions": "How should this step (irma) be packaged: Iterative assembly step for influenza and coronavirus?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow irma": null, "Local subworkflow IRMA": null}}, "target": "Local subworkflow IRMA", "target_idx": 3}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_3_0", "category": "samplesheet_schema", "state": {"assay": "PacBio HiFi unaligned BAM variant calling", "first_step": "PBMM2_ALIGN"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for PacBio HiFi unaligned BAM variant calling with entry step PBMM2_ALIGN.", "criteria": {"sample,bam": null, "sample,bam,bai": null, "sample,fastq_1": null, "sample,vcf": null}}, "target": "sample,bam", "target_idx": 0}
{"id": "noul_channel_operator_map_11", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.map { meta, reads -> [ meta, reads ] }` channel operator transforms channel emissions synchronously.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "resource_bcftools_norm_2", "category": "resource_profiling", "state": {"process": "BCFTOOLS_NORM", "tool": "bcftools/norm", "description": "Normalize VCF file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_NORM (Normalize VCF file) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "subworkflow_pkg_fastq_taxonomic_profile_metaphlan_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_TAXONOMIC_PROFILE_METAPHLAN", "modules": ["metaphlan/makedb", "metaphlan/metaphlan", "metaphlan/mergemetaphlantables"], "description": "Subworkflow to taxonomically classify metagenomic sequencing data using MetaPhlAn"}, "question": {"type": "choice", "instructions": "How should FASTQ_TAXONOMIC_PROFILE_METAPHLAN (metaphlan/makedb, metaphlan/metaphlan, metaphlan/mergemetaphlantables) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow FASTQ_TAXONOMIC_PROFILE_METAPHLAN": null, "Use nf-core subworkflow fastq_taxonomic_profile_metaphlan": null, "Leave them out": null}}, "target": "Use nf-core subworkflow fastq_taxonomic_profile_metaphlan", "target_idx": 2}
{"id": "qc_adapt_qc_aggregate_1_41", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Swap for NanoPlot": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "samplesheet_arch_bulk_rnaseq_se_5_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/rnaseq) for Single-end Illumina RNA-seq with strandedness. Input files: Single-end FASTQ reads per library.", "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/rnaseq, determine the input samplesheet column structure for: Single-end Illumina RNA-seq with strandedness.", "criteria": {"sample,fastq_1,strandedness": null, "sample,bam": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,vcf": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 0}
{"id": "intent_ask_question_6", "category": "intent_routing", "state": "Classify this user request: \"How does the .mix() operator differ from .combine() in Nextflow?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG"}}, "target": "ask_question", "target_idx": 0}
{"id": "samplesheet_arch_bulk_small_rna_3_4", "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": "Define the required samplesheet CSV header schema for Small RNA / miRNA sequencing with entry step FASTQC.", "criteria": {"sample,fastq_1,mirna_id": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "mod_find_unpigz_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A module for decompressing a large number of gzipped files, getting around the UNIX terminal argument limit (tools: find)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink2_extract": null, "find_unpigz": null, "pigz_compress": null, "star_genomegenerate": null, "crabz_compress": null}}, "target": "find_unpigz", "target_idx": 1}
{"id": "subworkflow_pkg_fastq_subsample_fq_salmon_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_SUBSAMPLE_FQ_SALMON", "modules": ["fq/subsample", "salmon/quant", "salmon/index"], "description": "Subsample fastq"}, "question": {"type": "choice", "instructions": "How should FASTQ_SUBSAMPLE_FQ_SALMON (fq/subsample, salmon/quant, salmon/index) be structured in DSL2?", "criteria": {"Leave them out": null, "Use nf-core subworkflow fastq_subsample_fq_salmon": null, "Keep the modules in the main workflow": null, "Local subworkflow FASTQ_SUBSAMPLE_FQ_SALMON": null}}, "target": "Use nf-core subworkflow fastq_subsample_fq_salmon", "target_idx": 1}
{"id": "qc_adapt_singlecell_multiqc_0_37", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For Multi-sample single-cell RNA-seq cohort, what is the recommended QC default for MultiQC?", "criteria": {"Keep MultiQC": null, "Keep FastQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "mod_deacon_indexdiff_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Subtract minimizers in deacon index (or fasta file) from another index (A - B) (tools: deacon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bismark/genomepreparation": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for ali", "bbmap/repair": "Re-pairs reads that became disordered or had some mates eliminated.", "biscuit/index": "Indexes a reference genome for use with Biscuit", "deacon/indexdiff": "Subtract minimizers in deacon index (or fasta file) from another index (A - B)", "sparsesignatures": "mutational signature deconvolution of cancer cells"}}, "target": "deacon/indexdiff", "target_idx": 3}
{"id": "qc_adapt_ffpe_wes_2_48", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_somalier_ancestry_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": {"kmcp_index": "Construct KMCP database from k-mer files", "atlas_pmd": "Estimate the post-mortem damage patterns of DNA", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "bbmap_repair": "Re-pairs reads that became disordered or had some mates eliminated.", "somalier_ancestry": "Somalier can extract informative sites, evaluate relatedness, and perform quality-control on BAM/CRAM/BCF/VCF/"}}, "target": "somalier_ancestry", "target_idx": 4}
{"id": "samplesheet_arch_ont_demux_barcodes_3_1", "category": "samplesheet_schema", "state": {"assay": "Multiplexed Oxford Nanopore run with barcode demultiplexing", "first_step": "NANOPLOT", "template": "nf-core/nanoseq"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Multiplexed Oxford Nanopore run with barcode demultiplexing with entry step NANOPLOT.", "criteria": {"sample,barcode,flowcell,kit,fastq": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,fastq_1": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 0}
{"id": "samplesheet_arch_spatial_xenium_3_3", "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": "Define the required samplesheet CSV header schema for 10x Xenium in situ subcellular spatial RNA transcriptomics with entry step INPUT_CHECK.", "criteria": {"sample,bam": null, "sample,image": 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": "intent_prepare_data_6", "category": "intent_routing", "state": "Classify this user request: \"I have 50 fastq.gz files in /data/raw. Can you construct a samplesheet.csv with sample, fastq_1, fastq_2, and strandedness columns?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes"}}, "target": "prepare_data", "target_idx": 3}
{"id": "mod_gubbins_1", "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": {"humann3_regroup": "Regrouping genes to other functional categories", "bbmap_repair": "Re-pairs reads that became disordered or had some mates eliminated.", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "gubbins": "Gubbins (Genealogies Unbiased By recomBinations In Nucleotide Sequences) is an algorithm that iteratively iden", "alignoth": "Creating alignment plots from bam files"}}, "target": "gubbins", "target_idx": 3}
{"id": "subworkflow_pkg_fasta_consensus_autocycler_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_CONSENSUS_AUTOCYCLER", "modules": ["autocycler/compress", "autocycler/cluster", "autocycler/trim", "autocycler/resolve", "autocycler/combine"], "description": "Generate consensus assemblies and assembly graphs from grouped contig FASTA files using autocycler"}, "question": {"type": "choice", "instructions": "How should FASTA_CONSENSUS_AUTOCYCLER (autocycler/compress, autocycler/cluster, autocycler/trim, autocycler/resolve, autocycler/combine) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow FASTA_CONSENSUS_AUTOCYCLER": null, "Use nf-core subworkflow fasta_consensus_autocycler": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fasta_consensus_autocycler", "target_idx": 2}
{"id": "qc_adapt_pe_illumina_fastqc_2_13", "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": "qc_adapt_illumina_novaseq_2_10", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "resource_antismash_antismashdownloaddatabases_1", "category": "resource_profiling", "state": {"process": "ANTISMASH_ANTISMASHDOWNLOADDATABASES", "tool": "antismash/antismashdownloaddatabases", "description": "antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynthesis gene clusters. This module downloads the antiSMASH databases for conda and docker/singularity runs."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANTISMASH_ANTISMASHDOWNLOADDATABASES (antiSMASH allows the rapid genome-wide identification, annotation and analysis o) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_nanoplot_1", "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": {"nanoplot": "Run NanoPlot on nanopore-sequenced reads", "octopusv_svcf2vcf": "Converts octopusv SVCF files to the standard VCF format", "busco_download": "Download database for BUSCO", "biscuit_qc": "Perform basic quality control on a BAM file generated with Biscuit", "samtools_cramsize": "List CRAM Content-ID and Data-Series sizes"}}, "target": "nanoplot", "target_idx": 0}
{"id": "samplesheet_arch_rnafusion_pe_2_0", "category": "samplesheet_schema", "state": {"technology": "Specialized RNA-seq", "workflow_entry": "FASTQC", "library_inputs": "Paired-end oncology RNA-seq reads for chimeric transcript discovery"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,fastq_2": null, "sample,fusion_bed": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 0}
{"id": "qc_adapt_qc_aggregate_2_35", "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_graphmap2_align_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A versatile pairwise aligner for genomic and spliced nucleotide sequences (tools: graphmap2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ampcombi": null, "graphmap2/align": null, "seqfu/check": null, "bamaligncleaner": null, "cnvkit/export": null}}, "target": "graphmap2/align", "target_idx": 1}
{"id": "resource_bismark_genomepreparation_1", "category": "resource_profiling", "state": {"process": "BISMARK_GENOMEPREPARATION", "tool": "bismark/genomepreparation", "description": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for alignments."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_GENOMEPREPARATION (Converts a specified reference genome into two different bisulfite\nconverted ver) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "noul_default_empty_channel_behavior_16", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `Channel.fromPath('data/*.fq')` emits an error if no files match the wildcard pattern by default.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_peka_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Runs PEKA CLIP peak k-mer analysis (tools: peka)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"peka": "Runs PEKA CLIP peak k-mer analysis", "quantify_pseudo_alignment": "Perform quantification with Salmon or Kallisto to produce count tables and SummarizedExperiment objects", "gatk4_variantrecalibrator": "Build a recalibration model to score variant quality for filtering purposes.\nIt is highly recommended to follo", "bedgraph_bedclip_bedgraphtobigwig": "Convert bedgraph to bigwig with clip", "clippy": "Runs the Clippy CLIP peak caller"}}, "target": "peka", "target_idx": 0}
{"id": "samplesheet_arch_chipseq_with_control_4_2", "category": "samplesheet_schema", "state": {"assay": "ChIP-seq with IP and input control design", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end FASTQ reads for immunoprecipitation and input chromatin?", "criteria": {"sample,antibody,control": null, "sample,fastq_1,fastq_2,antibody,control": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 1}
{"id": "resource_artic_guppyplex_3", "category": "resource_profiling", "state": {"process": "ARTIC_GUPPYPLEX", "tool": "artic/guppyplex", "description": "Aggregates fastq files with demultiplexed reads"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARTIC_GUPPYPLEX (Aggregates fastq files with demultiplexed reads) in conf/base.config?", "criteria": {"process_low": null, "process_high": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "subworkflow_pkg_fastq_fastqc_umitools_fastp_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_FASTQC_UMITOOLS_FASTP", "modules": ["fastqc", "umitools/extract", "fastp"], "description": "Read QC, UMI extraction and trimming"}, "question": {"type": "choice", "instructions": "How should FASTQ_FASTQC_UMITOOLS_FASTP (fastqc, umitools/extract, fastp) be structured in DSL2?", "criteria": {"Local subworkflow FASTQ_FASTQC_UMITOOLS_FASTP": null, "Use nf-core subworkflow fastq_fastqc_umitools_fastp": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fastq_fastqc_umitools_fastp", "target_idx": 1}
{"id": "mod_spring_compress_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Fast, efficient, lossless compression of FASTQ files. (tools: spring)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ariba_run": null, "spring_compress": null, "adapterremoval": null, "cellrangerarc_mkgtf": null, "dia_proteomics_analysis": null}}, "target": "spring_compress", "target_idx": 1}
{"id": "mod_concoct_concoctcoveragetable_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate the input coverage table for CONCOCT using a BEDFile (tools: concoct)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"genmap_map": null, "td2_predict": null, "concoct_concoctcoveragetable": null, "concoct_extractfastabins": null, "dastool_dastool": null}}, "target": "concoct_concoctcoveragetable", "target_idx": 2}
{"id": "mod_vcf2db_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A tool to create a Gemini-compatible DB file from an annotated VCF (tools: vcf2db)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"atlas_call": "generate VCF file from a BAM file using various calling methods", "vcf2db": "A tool to create a Gemini-compatible DB file from an annotated VCF", "trtools_mergestr": "MergeSTR merges multiple VCF files produced by the same TR genotyper into a single VCF file.", "gatk4_intervallisttobed": "Converts an Picard IntervalList file to a BED file.", "annotsv_annotsv": "Annotation and Ranking of Structural Variation"}}, "target": "vcf2db", "target_idx": 1}
{"id": "field_constraint_sex_2_4", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'sex' (Biological sex in pedigree/trio clinical analysis) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'sex' validated?", "criteria": {"type: boolean": null, "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": "resource_bigslice_bigslice_0", "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_high": null, "process_low": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "resource_angsd_gl_1", "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_medium": null, "process_high": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "noul_container_environment_specification_16", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"DSL2 `container` directives can specify Docker, Singularity, or Wave containers per process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "intent_debug_error_0", "category": "intent_routing", "state": "Classify this user request: \"My run failed with: Process `NFCORE_RNASEQ:RNASEQ:FASTQC (sample1)` terminated with an error exit status (137)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash"}}, "target": "debug_error", "target_idx": 3}
{"id": "qc_adapt_bulk_multiqc_0_42", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For High-throughput bulk WGS multi-sample run, what is the recommended QC default for MultiQC?", "criteria": {"Swap for NanoPlot": null, "Drop MultiQC": null, "Keep MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "qc_adapt_pacbio_hifi_0_44", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "samplesheet_arch_ont_demux_barcodes_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/nanoseq --input samplesheet.csv (Assay: Multiplexed Oxford Nanopore run with barcode demultiplexing)", "question": {"type": "choice", "instructions": "Which columns are standard for Multiplexed Oxford Nanopore run with barcode demultiplexing input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,barcode,flowcell,kit,fastq": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 3}
{"id": "pipe_all101_epitopeprediction_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for epitope. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"proteogenomicsdb": "The ProteoGenomics database generation workflow creates different protein databases for ProteoGenomics data analysis. [c", "methylseq": "Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair [bisulfi", "coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]", "callingcards": "A pipeline for processing calling cards data", "pacvar": "Longread PacBio sequencing processing for WGS and PureTarget [alignment, long-read, pacbio]", "metapep": "From metagenomes to epitopes and beyond", "bactmap": "A mapping-based pipeline for creating a phylogeny from bacterial whole genome sequences [bacteria, bacterial, bacterial-", "rnavar": "gatk4 RNA variant calling pipeline [gatk4, rna, rnaseq]", "viralintegration": "Analysis pipeline for the identification of viral integration events in genomes using a chimeric read approach. [chimeri", "epitopeprediction": "A bioinformatics best-practice analysis pipeline for epitope prediction and annotation [epitope, epitope-prediction, mhc"}}, "target": "epitopeprediction", "target_idx": 9}
{"id": "mod_zip_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compress file lists to produce ZIP archive files (tools: unzip)?", "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", "jellyfish/dump": "Dumps the results from a jellyfish binary file into a human readable format", "unzip": "Unzip ZIP archive files", "unzipfiles": "Unzip ZIP archive files", "zip": "Compress file lists to produce ZIP archive files"}}, "target": "zip", "target_idx": 4}
{"id": "subworkflow_pkg_tif_registration_stainwarpy_1", "category": "subworkflow_packaging", "state": {"subworkflow": "TIF_REGISTRATION_STAINWARPY", "modules": ["stainwarpy/extractchannel", "stainwarpy/register", "stainwarpy/transformsegmask"], "description": "Register H&E stained and multiplexed tissue images and transform segmentation masks using stainwarpy"}, "question": {"type": "choice", "instructions": "How should TIF_REGISTRATION_STAINWARPY (stainwarpy/extractchannel, stainwarpy/register, stainwarpy/transformsegmask) be structured in DSL2?", "criteria": {"Use nf-core subworkflow tif_registration_stainwarpy": null, "Local subworkflow TIF_REGISTRATION_STAINWARPY": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Use nf-core subworkflow tif_registration_stainwarpy", "target_idx": 0}
{"id": "noul_channel_factory_inside_process_body_1", "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_caalm_caalm_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Annotates carbohydrate-active enzyme (CAZyme) families from protein sequences\nusing protein language model (ESM) embeddings and FAISS-based nearest-neighbour\nsearch. Performs three-level hierarchical classification: binary CAZyme detection\n(Level 0), CAZy class assignment (Level 1), and CAZy family assignment (Level 2). (tools: caalm)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hifitrimmer_filterbam": "Run hifi_trimmer filter_bam to filter and trim adapter hits from PacBio HiFi reads (BAM/FASTA/FASTQ) using BLA", "rundbcan_database": "command from run_dbcan to prepare the database for dbCAN annotation.", "caalm_caalm": "Annotates carbohydrate-active enzyme (CAZyme) families from protein sequences\nusing protein language model (ES", "spotiflow": "Spotiflow, accurate and efficient spot detection with stereographic flow.", "rundbcan_easycgc": "CGC annotation module for the dbcan pipeline. This module is used to annotate carbohydrate-active enzymes (CAZ"}}, "target": "caalm_caalm", "target_idx": 2}
{"id": "core_tool_bwa_mem_described_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": {"star": "RNA-seq aligner", "bowtie2": "Short read aligner", "bwa_mem": "Burrows-Wheeler Aligner for short-read DNA mapping", "minimap2": "Long/short read aligner", "salmon": "Pseudo-aligner"}}, "target": "bwa_mem", "target_idx": 2}
{"id": "schema_std_atacseq_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/atacseq", "description": "ATAC-seq peak-calling and QC analysis pipeline", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/atacseq?", "criteria": {"sample,tools,file,index": null, "sample,nuclear_image,spot_table,membrane_image": null, "sample,fastq_1,fastq_2,replicate,control": null, "sample,bam,pbi,fail,repeat_id": null}}, "target": "sample,fastq_1,fastq_2,replicate,control", "target_idx": 2}
{"id": "noul_dynamic_resource_allocation_6", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process directive `cpus { check_max( 4 * task.attempt, 'cpus' ) }` allows dynamic resource scaling on task retry.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_openms_peptideindexer_1", "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_decoydatabase": "Create a decoy peptide database from a standard FASTA database.", "s4pred_runmodel": "Prediction of a protein's secondary structure from its amino acid sequence", "openms_peptideindexer": "Refreshes the protein references for all peptide hits.", "openms_idmerger": "Merges several idXML files into one idXML file.", "cooltools_insulation": "Calculate the diamond insulation scores and call insulating boundaries"}}, "target": "openms_peptideindexer", "target_idx": 2}
{"id": "mod_muscle_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: MUSCLE is a program for creating multiple alignments of amino acid or nucleotide sequences. A range of options are provided that give you the choice of optimizing accuracy, speed, or some compromise between the two (tools: muscle)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"canu": null, "muscle": null, "famsa_align": null, "famsa_guidetree": null, "picard_setnmmdanduqtags": null}}, "target": "muscle", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_2_5", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_zip_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compress file lists to produce ZIP archive files (tools: unzip)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"yak_count": null, "gunzip": null, "bcftools_roh": null, "zip": null, "unzip": null}}, "target": "zip", "target_idx": 3}
{"id": "qc_adapt_illumina_novaseq_2_18", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_adapterremoval_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Trim sequencing adapters and collapse overlapping reads (tools: adapterremoval)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cutadapt": null, "tabix/tabix": null, "adapterremoval": null, "gvcftools/extractvariants": null, "chopper": null}}, "target": "adapterremoval", "target_idx": 2}
{"id": "pipe_core10_scrnaseq_0_bare", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? Single-cell gene expression analysis for 10x Genomics Chromium data from FASTQ generation to UMI counts and Seurat matrices.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"rnaseq": null, "ampliseq": null, "taxprofiler": null, "atacseq": null, "viralrecon": null, "sarek": null, "scrnaseq": null, "eager": null, "chipseq": null, "mag": null}}, "target": "scrnaseq", "target_idx": 6}
{"id": "mod_primerprospector_analyzeprimers_0", "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": {"motus/preplong": "Taxonomic meta-omics profiling using universal marker genes", "icountmini/segment": "Formats a GTF file for use with iCount sigxls", "crabs/insilicopcr": "CRABS extracts the amplicon region of the primer set by conducting an in silico PCR.", "amrfinderplus/run": "Identify antimicrobial resistance in gene or protein sequences", "primerprospector/analyzeprimers": "Score PCR primers for binding to target sequences"}}, "target": "primerprospector/analyzeprimers", "target_idx": 4}
{"id": "samplesheet_arch_cancer_somatic_tn_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Somatic cancer variant calling with tumor-normal pairs)", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Somatic cancer variant calling with tumor-normal pairs with entry step BWA_MEM.", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "patient,sample,status,bam,bai": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 0}
{"id": "qc_adapt_bulk_multiqc_0_32", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For High-throughput bulk WGS multi-sample run, what is the recommended QC default for MultiQC?", "criteria": {"Swap for NanoPlot": null, "Drop MultiQC": null, "Keep MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_prinseqplusplus_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: PRINSEQ++ is a C++ implementation of the prinseq-lite.pl program. It can be used to filter, reformat or trim genomic and metagenomic sequence data (tools: prinseqplusplus)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamtofastq10x": "Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ATAC, Cell Ranger DNA, and Lon", "adapterremovalfixprefix": "Fixes prefixes from AdapterRemoval2 output to make sure no clashing read names are in the output. For use with", "sourmash_sketch": "Create a signature (a group of FracMinHash sketches) of a sequence using sourmash", "prinseqplusplus": "PRINSEQ++ is a C++ implementation of the prinseq-lite.pl program. It can be used to filter, reformat or trim g", "bedtools_shift": "Shifts each feature by specific number of bases"}}, "target": "prinseqplusplus", "target_idx": 3}
{"id": "resource_bigscape_bigscape_2", "category": "resource_profiling", "state": {"process": "BIGSCAPE_BIGSCAPE", "tool": "bigscape/bigscape", "description": "BiG-SCAPE (Biosynthetic Gene Similarity Clustering and Prospecting Engine) clusters\nbiosynthetic gene clusters (BGCs) into gene cluster families (GCFs) based on sequence\nsimilarity networks. It takes antiSMASH-annotated GenBank files and a Pfam database as\ninput, and produces similarity networks and clustering results."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIGSCAPE_BIGSCAPE (BiG-SCAPE (Biosynthetic Gene Similarity Clustering and Prospecting Engine) clust) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "intent_prepare_data_11", "category": "intent_routing", "state": "Classify this user request: \"I have 50 fastq.gz files in /data/raw. Can you construct a samplesheet.csv with sample, fastq_1, fastq_2, and strandedness columns?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": null, "build_pipeline": null, "prepare_data": null, "ask_question": null}}, "target": "prepare_data", "target_idx": 2}
{"id": "intent_prepare_data_16", "category": "intent_routing", "state": "Classify this user request: \"I have 50 fastq.gz files in /data/raw. Can you construct a samplesheet.csv with sample, fastq_1, fastq_2, and strandedness columns?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash"}}, "target": "prepare_data", "target_idx": 0}
{"id": "subworkflow_pkg_bam_sort_stats_samtools_2", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_SORT_STATS_SAMTOOLS", "modules": ["samtools/sort", "samtools/index", "samtools/stats", "samtools/idxstats", "samtools/flagstat", "bam_stats_samtools"], "description": "Sort SAM/BAM/CRAM file"}, "question": {"type": "choice", "instructions": "How should BAM_SORT_STATS_SAMTOOLS (samtools/sort, samtools/index, samtools/stats, samtools/idxstats, samtools/flagstat, bam_stats_samtools) be structured in DSL2?", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow BAM_SORT_STATS_SAMTOOLS": null, "Use nf-core subworkflow bam_sort_stats_samtools": null}}, "target": "Use nf-core subworkflow bam_sort_stats_samtools", "target_idx": 3}
{"id": "samplesheet_arch_cancer_longitudinal_0_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/oncoanalyser", "assay_type": "Longitudinal cancer monitoring across multiple timepoints", "data_format": "Serial plasma cfDNA and biopsy FASTQs across treatment intervals"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Longitudinal cancer monitoring across multiple timepoints?", "criteria": {"patient,sample,bam": null, "sample,timepoint,fastq": null, "sample,fastq_1,fastq_2": null, "patient,sample,timepoint,status,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,status,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_cellsnp_modea_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Cellsnp-lite is a C/C++ tool for efficient genotyping bi-allelic SNPs on single cells. You can use the mode A of cellsnp-lite after read alignment to obtain the snp x cell pileup UMI or read count matrices for each alleles of given or detected SNPs for droplet based single cell data. (tools: cellsnp)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cellsnp/modea": null, "sequencetools/pileupcaller": null, "gatk4/unmarkduplicates": null, "pypgx/runngspipeline": null, "bedtools/closest": null}}, "target": "cellsnp/modea", "target_idx": 0}
{"id": "mod_deepvariant_vcfstatsreport_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_vcfstatsreport": "DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generat", "bcftools_consensus": "Compresses VCF files", "ribocode_prepare": "Prepare the annotation files for RiboCode ORF calling", "ucsc_wigtobigwig": "Convert ascii format wig file to binary big wig format", "aardvark_merge": "A tool to evaluate and merge multiple variant calls into a consensus VCF."}}, "target": "deepvariant_vcfstatsreport", "target_idx": 0}
{"id": "mod_samtools_mpileup_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate text pileup output for one or multiple BAM files. Each input file produces a separate group of pileup columns in the output. (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samtools/mpileup": null, "gatk4/gatherpileupsummaries": null, "aria2": null, "sambamba/flagstat": null, "sequencetools/pileupcaller": null}}, "target": "samtools/mpileup", "target_idx": 0}
{"id": "mod_hypo_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Assembly polisher using short (and long) reads (tools: hypo)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vt/decompose": null, "hypo": null, "parabricks/indexgvcf": null, "abra2": null, "abricate/summary": null}}, "target": "hypo", "target_idx": 1}
{"id": "subworkflow_pkg_differential_functional_enrichment_2", "category": "subworkflow_packaging", "state": {"subworkflow": "DIFFERENTIAL_FUNCTIONAL_ENRICHMENT", "modules": ["gprofiler2/gost", "gsea/gsea", "decoupler/decoupler", "propr/grea", "custom/tabulartogseagct", "custom/tabulartogseacls", "custom/tabulartogseachip"], "description": "Run functional analysis on differential abundance analysis output"}, "question": {"type": "choice", "instructions": "How should DIFFERENTIAL_FUNCTIONAL_ENRICHMENT (gprofiler2/gost, gsea/gsea, decoupler/decoupler, propr/grea, custom/tabulartogseagct, custom/tabulartogseacls, custom/tabulartogseachip) be structured in DSL2?", "criteria": {"Local subworkflow DIFFERENTIAL_FUNCTIONAL_ENRICHMENT": null, "Use nf-core subworkflow differential_functional_enrichment": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Use nf-core subworkflow differential_functional_enrichment", "target_idx": 1}
{"id": "mod_ultra_pipeline_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: uLTRA aligner - A wrapper around minimap2 to improve small exon detection (tools: ultra)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ultra_pipeline": "uLTRA aligner - A wrapper around minimap2 to improve small exon detection", "orthofinder": "OrthoFinder is a fast, accurate and comprehensive platform for comparative genomics.", "biscuit_index": "Indexes a reference genome for use with Biscuit", "centrifuge_build": "Build centrifuge database for taxonomic profiling", "biscuit_qc": "Perform basic quality control on a BAM file generated with Biscuit"}}, "target": "ultra_pipeline", "target_idx": 0}
{"id": "resource_artic_guppyplex_2", "category": "resource_profiling", "state": {"process": "ARTIC_GUPPYPLEX", "tool": "artic/guppyplex", "description": "Aggregates fastq files with demultiplexed reads"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ARTIC_GUPPYPLEX (Aggregates fastq files with demultiplexed reads) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "schema_std_isoseq_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/isoseq", "description": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences and produce a bed annotation. ", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/isoseq?", "criteria": {"sample,alleles,mhc_class,filename": null, "sample,seq_data,pbi,start_from": null, "sample,fastq,cell_count": null, "sample,fastq_1,fastq_2,fastq_barcode,expected_cells": null}}, "target": "sample,seq_data,pbi,start_from", "target_idx": 1}
{"id": "samplesheet_arch_rnafusion_pe_0_4", "category": "samplesheet_schema", "state": {"technology": "Specialized RNA-seq", "workflow_entry": "FASTQC", "library_inputs": "Paired-end oncology RNA-seq reads for chimeric transcript discovery"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: RNA gene fusion detection (Arriba, STAR-Fusion)?", "criteria": {"sample,fastq_1,fastq_2,strandedness": null, "sample,fusion_bed": null, "sample,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 0}
{"id": "mod_fgumi_filter_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filters consensus reads generated by simplex or duplex consensus calling.\nThis is a high-performance replacement for fgbio FilterConsensusReads. (tools: fgumi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"jellyfish_dump": "Dumps the results from a jellyfish binary file into a human readable format", "fgumi_filter": "Filters consensus reads generated by simplex or duplex consensus calling.\nThis is a high-performance replaceme", "fgbio_copyumifromreadname": "Copies the UMI at the end of a bam files read name to the RX tag.", "centrifuge_build": "Build centrifuge database for taxonomic profiling", "fgbio_zipperbams": "FGBIO tool to zip together an unmapped and mapped BAM to transfer metadata into the output BAM"}}, "target": "fgumi_filter", "target_idx": 1}
{"id": "mod_deepvariant_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: (DEPRECATED - see main.nf) DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data (tools: deepvariant)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_consensus": "Compresses VCF files", "aardvark_compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "fasta_build_add_kraken2_bracken": "KRAKEN2 and BRACKEN build custom database subworkflow", "gatk4_combinegvcfs": "Combine per-sample gVCF files produced by HaplotypeCaller into a multi-sample gVCF file", "deepvariant": "DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generat"}}, "target": "deepvariant", "target_idx": 4}
{"id": "mod_jvarkit_vcf2table_1", "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": {"jvarkit_vcf2table": "Convert VCF to a user friendly table", "atlas_call": "generate VCF file from a BAM file using various calling methods", "tidk_explore": "`tidk explore` attempts to find the simple telomeric repeat unit in the genome provided.\nIt will report this r", "graphmap2_index": "A versatile pairwise aligner for genomic and spliced nucleotide sequences", "annotsv_annotsv": "Annotation and Ranking of Structural Variation"}}, "target": "jvarkit_vcf2table", "target_idx": 0}
{"id": "mod_deeparg_predict_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A deep learning based approach to predict Antibiotic Resistance Genes (ARGs) from metagenomes (tools: deeparg)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"snpsift_annmem": "Annotate VCF files using pre-built SnpSift annMem databases.\nEnriches input VCF records by querying memory-opt", "deeparg_downloaddata": "A deep learning based approach to predict Antibiotic Resistance Genes (ARGs) from metagenomes", "abricate_run": "Screen assemblies for antimicrobial resistance against multiple databases", "deeparg_predict": "A deep learning based approach to predict Antibiotic Resistance Genes (ARGs) from metagenomes", "biscuit_pileup": "Computes cytosine methylation and callable SNV mutations, optionally in reference to a germline BAM to call so"}}, "target": "deeparg_predict", "target_idx": 3}
{"id": "noul_undeclared_process_file_inputs_15", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Processes in Nextflow DSL2 can directly access files on the host filesystem without declaring them in `input:`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "mod_ilastik_pixelclassification_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Ilastik is a tool that utilizes machine learning algorithms to classify pixels, segment, track and count cells in images. Ilastik contains a graphical user interface to interactively label pixels. However, this nextflow module will implement the --headless mode, to apply pixel classification using a pre-trained .ilp file on an input image. (tools: ilastik)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"krakentools/extractkrakenreads": "Extract reads classified at any user-specified taxonomy IDs.", "ilastik/pixelclassification": "Ilastik is a tool that utilizes machine learning algorithms to classify pixels, segment, track and count cells", "numorph/3dunet": "3DUnet for cell nuclei quantification on 3D microscopy images of the numorph toolkit.", "coreograph": "Great....yet another TMA dearray program. What does this one do? Coreograph uses UNet, a deep learning model, ", "agat/spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th"}}, "target": "ilastik/pixelclassification", "target_idx": 1}
{"id": "field_constraint_status_2_11", "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, "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": "resource_anndata_getsize_3", "category": "resource_profiling", "state": {"process": "ANNDATA_GETSIZE", "tool": "anndata/getsize", "description": "Get the size (n_cells or n_genes) of an anndata object stored as a h5ad file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANNDATA_GETSIZE (Get the size (n_cells or n_genes) of an anndata object stored as a h5ad file) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "noul_executor_support_4", "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": "resource_anota2seq_anota2seqrun_0", "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_medium": null, "process_long": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "pipe_all101_fastquorum_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for consensus analysis? Specific context: 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": {"fastquorum": "Pipeline to produce consensus reads using unique molecular indexes/barcodes (UMIs) [consensus, umi, umis]", "airrflow": "B-cell and T-cell Adaptive Immune Receptor Repertoire (AIRR) sequencing analysis pipeline using the Immcantation framewo", "createtaxdb": "Parallelised and automated construction of metagenomic classifier databases of different tools [database, database-build", "rnadnavar": "Pipeline for RNA and DNA integrated analysis for somatic mutation detection", "methylong": "Extract methylation calls from long reads (ONT/ PacBio)  [dna-methylation, fiber-seq, long-read]", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline [adna, ancient-dna-analysis, ancientdna]", "nascent": "Nascent Transcription Processing Pipeline [gro-seq, nascent, pro-seq]", "demultiplex": "Demultiplexing pipeline for sequencing data [bases2fastq, bcl2fastq, demultiplexing]", "imcyto": "Image Mass Cytometry analysis pipeline [cytometry, image-analysis, image-processing]", "lsmquant": "A pipeline for processing and analysis of light-sheet microscopy images. [3dunet, image-analysis, image-processing]"}}, "target": "fastquorum", "target_idx": 0}
{"id": "mod_bcftools_convert_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts certain output formats to VCF (tools: bcftools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools/index": null, "bcftools/convert": null, "bcftools/concat": null, "gatk4/splitintervals": null, "deeptools/plotpca": null}}, "target": "bcftools/convert", "target_idx": 1}
{"id": "qc_adapt_pacbio_hifi_2_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": "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_bacterial_hybrid_assembly_0_0", "category": "samplesheet_schema", "state": {"assay": "Hybrid bacterial assembly combining short Illumina and long Nanopore reads", "first_step": "FASTQC", "inputs": "Illumina paired-end reads paired with Oxford Nanopore long reads per isolate", "pipeline": "nf-core/bacass"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Hybrid bacterial assembly combining short Illumina and long Nanopore reads?", "criteria": {"sample,fastq_1": null, "sample,fasta": null, "sample,fastq_1,fastq_2,long_fastq": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 2}
{"id": "mod_krakentools_kreport2krona_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Takes a Kraken report file and prints out a krona-compatible TEXT file (tools: krakentools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bbmap/bbnorm": null, "agat/spextractsequences": null, "krona/ktupdatetaxonomy": null, "centrifuge/kreport": null, "krakentools/kreport2krona": null}}, "target": "krakentools/kreport2krona", "target_idx": 4}
{"id": "field_constraint_fastq_2_3_1", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "fastq_2", "validation_type": "conditional_file_pattern"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'fastq_2'.", "criteria": {"pattern: ^\\S+\\.bam$": null, "type: required string": null, "enum: [0, 1]": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 3}
{"id": "field_constraint_strandedness_3_12", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "strandedness", "validation_type": "categorical_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'strandedness'.", "criteria": {"format: file-path": null, "type: boolean": null, "pattern: ^[0-9]+$": null, "enum: [auto, forward, reverse, unstranded]": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 3}
{"id": "resource_bedtools_maskfasta_4", "category": "resource_profiling", "state": {"process": "BEDTOOLS_MASKFASTA", "tool": "bedtools/maskfasta", "description": "masks sequences in a FASTA file based on intervals defined in a feature file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_MASKFASTA (masks sequences in a FASTA file based on intervals defined in a feature file.) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_cancer_longitudinal_1_3", "category": "samplesheet_schema", "state": {"assay": "Longitudinal cancer monitoring across multiple timepoints", "first_step": "FASTQC", "inputs": "Serial plasma cfDNA and biopsy FASTQs across treatment intervals"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Longitudinal cancer monitoring across multiple timepoints?", "criteria": {"patient,sample,bam": null, "sample,fastq_1,fastq_2": null, "patient,sample,timepoint,status,fastq_1,fastq_2": null, "sample,timepoint,fastq": null}}, "target": "patient,sample,timepoint,status,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_bedops_gtf2bed_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert gtf format to bed format (tools: gtf2bed)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bedops/gtf2bed": "Convert gtf format to bed format", "agat/convertspgff2gtf": "Converts a GFF/GTF file into a proper GTF file", "minibwa/map": "Align fastq reads to a fasta reference using minibwa", "custom/dumpsoftwareversions": "Custom module used to dump software versions within the nf-core pipeline template", "agat/spkeeplongestisoform": "Filters GFF records to keep only the longest isoform per gene"}}, "target": "bedops/gtf2bed", "target_idx": 0}
{"id": "mod_varlociraptor_preprocess_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Obtains per-sample observations for the actual calling process with varlociraptor calls (tools: varlociraptor)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"segemehl/align": "A multi-split mapping algorithm for circular RNA, splicing, trans-splicing and fusion detection", "varlociraptor/callvariants": "Call variants for a given scenario specified with the varlociraptor calling grammar, preprocessed by varlocira", "varlociraptor/preprocess": "Obtains per-sample observations for the actual calling process with varlociraptor calls", "hisat2/align": "Align RNA-Seq reads to a reference with HISAT2", "bedgovcf": "Convert a BED file to a VCF file according to a YAML config"}}, "target": "varlociraptor/preprocess", "target_idx": 2}
{"id": "resource_ale_1", "category": "resource_profiling", "state": {"process": "ALE", "tool": "ale", "description": "ALE: assembly likelihood estimator."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ALE (ALE: assembly likelihood estimator.) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "subworkflow_pkg_bed_scatter_bedtools_1", "category": "subworkflow_packaging", "state": {"subworkflow": "BED_SCATTER_BEDTOOLS", "modules": ["bedtools/split"], "description": "Scatters inputted BED files by the amount specified."}, "question": {"type": "choice", "instructions": "How should BED_SCATTER_BEDTOOLS (bedtools/split) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Use nf-core subworkflow bed_scatter_bedtools": null, "Local subworkflow BED_SCATTER_BEDTOOLS": null, "Leave them out": null}}, "target": "Use nf-core subworkflow bed_scatter_bedtools", "target_idx": 1}
{"id": "qc_adapt_illumina_novaseq_0_20", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Illumina NovaSeq X paired-end 150bp WGS, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "qc_adapt_targeted_amplicon_2_14", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "samplesheet_arch_cageseq_transcription_4_5", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/cageseq", "assay_type": "CAGE-seq 5-prime capped transcript end sequencing", "data_format": "Single-end capped 5-prime cDNA tags for transcription start site (TSS) mapping"}, "question": {"type": "choice", "instructions": "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_chipseq_with_control_0_1", "category": "samplesheet_schema", "state": {"assay": "ChIP-seq with IP and input control design", "first_step": "FASTQC", "inputs": "Paired-end FASTQ reads for immunoprecipitation and input chromatin"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: ChIP-seq with IP and input control design?", "criteria": {"sample,fastq_1,fastq_2,antibody,control": null, "sample,fastq_1": null, "sample,bam": null, "sample,antibody,control": null}}, "target": "sample,fastq_1,fastq_2,antibody,control", "target_idx": 0}
{"id": "mod_fastq_contam_seqtk_kraken_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Produces a contamination report from FastQ input after subsampling (tools: fastq_contam_seqtk_kraken)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"assemblyscan": null, "whatshap_haplotag": null, "fastq_contam_seqtk_kraken": null, "bedtools_jaccard": null, "metaphlan3_mergemetaphlantables": null}}, "target": "fastq_contam_seqtk_kraken", "target_idx": 2}
{"id": "field_constraint_sex_3_0", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "sex", "validation_type": "pedigree_sex_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'sex'.", "criteria": {"format: file-path": null, "enum: [1, 2, other, unknown] (1=male, 2=female)": null, "type: boolean": null, "pattern: ^\\S+\\.gz$": null}}, "target": "enum: [1, 2, other, unknown] (1=male, 2=female)", "target_idx": 1}
{"id": "pipe_all101_molkart_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze A pipeline for processing Molecular Cartography data from Resolve Bioscience (combinatorial FISH). Topics: fish, image-processing, imaging, molecularcartography, segmentation, single-cell. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"cutandrun": null, "demultiplex": null, "taxprofiler": null, "variantbenchmarking": null, "metatdenovo": null, "mag": null, "molkart": null, "viralrecon": null, "sarek": null, "smrnaseq": null}}, "target": "molkart", "target_idx": 6}
{"id": "noul_multiple_script_sections_invalid_6", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"A process definition in Nextflow can declare multiple `script:` sections within the same process block.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "qc_adapt_targeted_amplicon_0_23", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "noul_dynamic_resource_allocation_23", "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": "qc_adapt_pe_illumina_fastqc_2_6", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Standard Paired-end Illumina RNA-seq (short_reads_150bp).", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_traitar_pfamget_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Download PFAM database for traitar phenotype prediction (tools: traitar)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"antismash/antismashlitedownloaddatabases": "antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynt", "cooler/digest": "Generate fragment-delimited genomic bins", "minimap2/align": "A versatile pairwise aligner for genomic and spliced nucleotide sequences", "bigslice/downloaddb": "Downloads and extracts the BiG-SLiCE HMM database (biosynthetic and sub Pfams)\nusing the bundled `download_big", "traitar/pfamget": "Download PFAM database for traitar phenotype prediction"}}, "target": "traitar/pfamget", "target_idx": 4}
{"id": "pipe_all101_ampliseq_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for 16s analysis? Specific context: Amplicon sequencing analysis workflow using DADA2 and QIIME2. Topics: 16s, 18s, amplicon-sequencing, edna, illumina, iontorrent. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"metapep": "From metagenomes to epitopes and beyond", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 [16s, 18s, amplicon-sequencing]", "genomeqc": "Compare the quality of multiple genomes, along with their annotations. [genome-assembly-evaluation, genomics, phylogenet", "hgtseq": "A pipeline to investigate horizontal gene transfer from NGS data [bwa-mem, bwa-mem2, fastqc]", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina"}}, "target": "ampliseq", "target_idx": 1}
{"id": "mod_plink2_pmerge_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge a second PLINK 2 fileset into the first and write a new combined PLINK 2 fileset (tools: plink2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink2_pmerge": "Merge a second PLINK 2 fileset into the first and write a new combined PLINK 2 fileset", "minimap2_index": "Provides fasta index required by minimap2 alignment.", "plink2_filter": "Filters plink bfiles or pfiles with filters such as maf or var", "parabricks_rnafq2bam": "This tool is the equivalent of fq2bam for RNA-Seq samples, receiving inputs in FASTQ format, performing alignm", "plink2_pca": "Perform PCA analysis using PLINK"}}, "target": "plink2_pmerge", "target_idx": 0}
{"id": "resource_bases2fastq_3", "category": "resource_profiling", "state": {"process": "BASES2FASTQ", "tool": "bases2fastq", "description": "Demultiplex Element Biosciences bases files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BASES2FASTQ (Demultiplex Element Biosciences bases files) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_bulk_rnaseq_pe_3_0", "category": "samplesheet_schema", "state": {"assay": "Paired-end Illumina RNA-seq with strandedness", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Paired-end Illumina RNA-seq with strandedness with entry step FASTQC.", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 1}
{"id": "schema_std_proteinfold_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/proteinfold", "assay": "proteinfold pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/proteinfold (Protein 3D structure prediction pipeline)?", "criteria": {"gene_name,alignment,tree,suite,tool": null, "id,fasta,sequence": null, "condition,type,microbiome_path,alleles,weights_path": null, "sample,fastq_1,fastq_2,fasta,run_accession": null}}, "target": "id,fasta,sequence", "target_idx": 1}
{"id": "samplesheet_arch_rare_disease_trio_5_3", "category": "samplesheet_schema", "state": {"assay": "Trio exome/genome sequencing (Proband, Mother, Father)", "first_step": "FASTQC", "inputs": "Paired-end FASTQs with pedigree relationships and affected status"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/raredisease, determine the input samplesheet column structure for: Trio exome/genome sequencing (Proband, Mother, Father).", "criteria": {"sample,bam,bai": null, "patient,sample,status,fastq_1,fastq_2": null, "family_id,sample,fastq_1,fastq_2": null, "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2": null}}, "target": "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_hmmer_hmmalign_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: hmmalign from the HMMER suite aligns a number of sequences to an HMM profile (tools: hmmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hmmer/hmmalign": null, "gappa/examineheattree": null, "bwa/mem": null, "ashlar": null, "coverm/contig": null}}, "target": "hmmer/hmmalign", "target_idx": 0}
{"id": "mod_bam_create_som_pon_gatk_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform variant calling on a set of normal samples using mutect2 panel of normals mode. Group them into a genomicsdbworkspace using genomicsdbimport, then use this to create a panel of normals using createsomaticpanelofnormals. (tools: bam_create_som_pon_gatk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bam_create_som_pon_gatk": null, "gatk4/annotateintervals": null, "bamclipper": null, "gatk4/applyvqsr": null, "hicexplorer/hicpca": null}}, "target": "bam_create_som_pon_gatk", "target_idx": 0}
{"id": "samplesheet_arch_pacbio_hifi_wgs_0_1", "category": "samplesheet_schema", "state": {"assay": "Long-read Pacific Biosciences HiFi sequencing", "first_step": "HIFIADAPTERFILT", "inputs": "Single HiFi BAM or FastQ"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Long-read Pacific Biosciences HiFi sequencing?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,vcf": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "samplesheet_arch_prealigned_cram_indexed_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Genome analysis from reference-compressed CRAM files)", "question": {"type": "choice", "instructions": "Which columns are standard for Genome analysis from reference-compressed CRAM files input samplesheet?", "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_pacbio_hifi_1_9", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "noul_named_output_channel_access_7", "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": "field_constraint_sample_1_4", "category": "samplesheet_schema", "state": {"column": "sample", "purpose": "Sample identifier across all nf-core pipelines"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'sample' (Sample identifier across all nf-core pipelines).", "criteria": {"format: file-path": null, "type: integer": null, "enum: [0, 1]": null, "pattern: ^\\S+$ (no whitespace, unique)": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 3}
{"id": "qc_adapt_bulk_multiqc_2_42", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Drop MultiQC": null, "Swap for NanoPlot": null, "Keep FastQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "qc_adapt_ont_nanoplot_2_2", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_genmod_models_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: annotate models of inheritance (tools: genmod)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"genmod/models": null, "macsyfinder/download": null, "pairtools/select": null, "genmod/annotate": null, "multiqc": null}}, "target": "genmod/models", "target_idx": 0}
{"id": "mod_rseqc_bamstat_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate statistics from a bam file (tools: rseqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"allelecounter": "Generates a count of coverage of alleles", "rseqc/bamstat": "Generate statistics from a bam file", "bamclipper": "This module is used to clip primer sequences from your alignments.", "atlas/pmd": "Estimate the post-mortem damage patterns of DNA", "clipkit": "A multiple sequence alignment-trimming algorithm for accurate phylogenomic inference."}}, "target": "rseqc/bamstat", "target_idx": 1}
{"id": "samplesheet_arch_epigenomics_hic_5_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/hic --input samplesheet.csv (Assay: Hi-C chromosome conformation capture mapping)", "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,matrix,contacts": null, "sample,fastq_1": null, "sample,bed": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_methurator_gtestimator_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run estimator for DNA methylation sequencing saturation. (tools: methurator)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"methurator/plot": "Plots results produced by methurator gtestimator.", "bismark/genomepreparation": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for ali", "sentieon/haplotyper": "Runs Sentieon's haplotyper for germline variant calling.", "bcftools/index": "Index VCF tools", "methurator/gtestimator": "Run estimator for DNA methylation sequencing saturation."}}, "target": "methurator/gtestimator", "target_idx": 4}
{"id": "mod_gatk4_determinegermlinecontigploidy_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Determines the baseline contig ploidy for germline samples given counts data (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cnaqc": null, "cnvkit/antitarget": null, "pharokka/pharokka": null, "mitorsaw/haplotype": null, "gatk4/determinegermlinecontigploidy": null}}, "target": "gatk4/determinegermlinecontigploidy", "target_idx": 4}
{"id": "mod_survivor_merge_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compare or merge VCF files to generate a consensus or multi sample VCF files. (tools: survivor)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_merge": "Merge VCF files", "bclconvert": "Demultiplex Illumina BCL files", "tcoffee_consensus": "Computes a consensus alignment using T_COFFEE", "survivor_merge": "Compare or merge VCF files to generate a consensus or multi sample VCF files.", "agat_spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated"}}, "target": "survivor_merge", "target_idx": 3}
{"id": "mod_xengsort_index_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Fast lightweight accurate xenograft sorting (tools: xengsort)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biscuit_index": null, "rsem_calculateexpression": null, "bcftools_index": null, "xengsort_index": null, "parabricks_fq2bammeth": null}}, "target": "xengsort_index", "target_idx": 3}
{"id": "schema_std_createtaxdb_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/createtaxdb. Description: Parallelised and automated construction of metagenomic classifier databases of different tools.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/createtaxdb.", "criteria": {"sample,fastq_1,fastq_2": null, "ID,Sample,Condition,ReplicateFileName,Fasta": null, "id,taxid,fasta_dna,fasta_aa": null, "sample,fastq_1,fastq_2,sampleID,forwardReads": null}}, "target": "id,taxid,fasta_dna,fasta_aa", "target_idx": 2}
{"id": "mod_varlociraptor_estimatealignmentproperties_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: In order to judge about candidate indel and structural variants, Varlociraptor needs to know about certain properties of the underlying sequencing experiment in combination with the used read aligner. (tools: varlociraptor)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_convertbed2gff": "Takes a bed12 file and converts to a GFF3 file", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "varlociraptor_estimatealignmentproperties": "In order to judge about candidate indel and structural variants, Varlociraptor needs to know about certain pro", "ashlar": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration", "orfipy": "orfipy is a tool written in python/cython to extract ORFs in an extremely and fast and flexible manner."}}, "target": "varlociraptor_estimatealignmentproperties", "target_idx": 2}
{"id": "resource_bwa_index_2", "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_single": null, "process_long": null, "process_high": null, "process_low": null}}, "target": "process_high", "target_idx": 2}
{"id": "qc_adapt_ffpe_wes_1_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": "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_methylseq_bisulfite_5_5", "category": "samplesheet_schema", "state": {"assay": "Whole-Genome Bisulfite Sequencing (WGBS / EM-seq)", "first_step": "FASTQC", "template": "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,fastq_1": null, "sample,vcf": null, "sample,fastq_1,fastq_2": null, "sample,cpg,methylation": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_custom_clustermetrics_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Computes clustering quality metrics (silhouette, Calinski-Harabasz, Davies-Bouldin) and performs k-sweep analysis (tools: scikit-learn)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom_clustermetrics": "Computes clustering quality metrics (silhouette, Calinski-Harabasz, Davies-Bouldin) and performs k-sweep analy", "foldmason_easymsa": "Aligns protein structures using foldmason", "custom_clustervisualization": "Generates UMAP and t-SNE visualizations colored by cluster", "bigscape_bigscape": "BiG-SCAPE (Biosynthetic Gene Similarity Clustering and Prospecting Engine) clusters\nbiosynthetic gene clusters", "ampcombi": "A tool to parse and summarise results from antimicrobial peptides tools and present functional classification."}}, "target": "custom_clustermetrics", "target_idx": 0}
{"id": "mod_biscuit_bsconv_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Summarize and/or filter reads based on bisulfite conversion rate (tools: biscuit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hmmer_jackhmmer": "iterative searches to detect distant homologs by refining an HMM profile from hits", "biscuit_qc": "Perform basic quality control on a BAM file generated with Biscuit", "biscuit_align": "Aligns single- or paired-end reads from bisulfite-converted libraries to a reference genome using Biscuit.", "seqfu_stats": "Statistics for FASTA or FASTQ files", "biscuit_bsconv": "Summarize and/or filter reads based on bisulfite conversion rate"}}, "target": "biscuit_bsconv", "target_idx": 4}
{"id": "mod_perbase_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Per-base metrics on BAM/CRAM files. (tools: perbase)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamclipper": "This module is used to clip primer sequences from your alignments.", "perbase": "Per-base metrics on BAM/CRAM files.", "quast": "Quality Assessment Tool for Genome Assemblies", "peka": "Runs PEKA CLIP peak k-mer analysis", "abra2": "Assembly Based ReAligner for next-generation sequencing data"}}, "target": "perbase", "target_idx": 1}
{"id": "samplesheet_arch_pediatric_trio_somatic_4_4", "category": "samplesheet_schema", "state": {"technology": "Clinical Genetics", "workflow_entry": "FASTQC", "library_inputs": "Paired-end FASTQs tracking patient, sample, tissue status (normal/tumor), and maternal/paternal lineage"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end FASTQs tracking patient, sample, tissue status (normal/tumor), and maternal/paternal lineage?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "family_id,sample,fastq_1,fastq_2": null, "family_id,patient,sample,status,sex,fastq_1,fastq_2": null}}, "target": "family_id,patient,sample,status,sex,fastq_1,fastq_2", "target_idx": 3}
{"id": "resource_bcftools_pluginvcf2table_0", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINVCF2TABLE", "tool": "bcftools/pluginvcf2table", "description": "Converts VCF/BCF files into a tab-delimited table using the bcftools +vcf2table plugin.\nEach variant is output as one row, with INFO and FORMAT fields as columns."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINVCF2TABLE (Converts VCF/BCF files into a tab-delimited table using the bcftools +vcf2table ) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_metamdbg_asm_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Metagenome assembler for long-read sequences (HiFi and ONT). (tools: metamdbg)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ale": null, "umitools_extract": null, "abricate_run": null, "metamdbg_asm": null, "kallistobustools_ref": null}}, "target": "metamdbg_asm", "target_idx": 3}
{"id": "mod_civicpy_annotate_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A python client and analysis toolkit to annotate variants with information from the Clinical Interpretations of Variants in Cancer (CIViC) knowledgebase (tools: civicpy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_spfilterfeaturefromkilllist": null, "civicpy_annotate": null, "agat_spfilterbyorfsize": null, "crabz_compress": null, "raw2ometiff": null}}, "target": "civicpy_annotate", "target_idx": 1}
{"id": "schema_std_riboseq_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/riboseq", "assay": "riboseq pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/riboseq (Pipeline for the analysis of ribosome profiling, or Ribo-seq)?", "criteria": {"sample,type,level,msfile": null, "sample,fastq_1,fastq_2,strandedness,type": null, "sample,sample_id,fastq_1,fastq_2,method": null, "sample,fastq_1,fastq_2,strandedness,seq_platform": null}}, "target": "sample,fastq_1,fastq_2,strandedness,type", "target_idx": 1}
{"id": "mod_svaba_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: SvABA is an efficient and accurate method for detecting SVs from short-read sequencing data using genome-wide local assembly with low memory and computing requirements (tools: svaba)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"svaba": "SvABA is an efficient and accurate method for detecting SVs from short-read sequencing data using genome-wide ", "dysgu_run": "Dysgu calls structural variants (SVs) from mapped sequencing reads. It is designed for accurate and efficient ", "caddsv_run": "Score structural variants with CADD-SV.", "rpbp_estimateorfbayesfactors": "Score every candidate ORF for evidence of active translation. For\neach ORF, Rp-Bp fits two competing Bayesian ", "skani_search": "Memory-efficient ANI database queries with skani."}}, "target": "svaba", "target_idx": 0}
{"id": "intent_debug_error_2", "category": "intent_routing", "state": "Classify this user request: \"My run failed with: Process `NFCORE_RNASEQ:RNASEQ:FASTQC (sample1)` terminated with an error exit status (137)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules"}}, "target": "debug_error", "target_idx": 0}
{"id": "noul_dynamic_resource_allocation_13", "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_trtools_dumpstr_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: DumpSTR filters VCF files with TR genotypes, performing call-level and locus-level filtering, and outputs a filtered VCF file. (tools: trtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ncbitools_vecscreen": "NCBI tool for detecting vector contamination in nucleic acid sequences. This tool is older than NCBI's FCS-ada", "seqkit_rmdup": "Transforms sequences (extract ID, filter by length, remove gaps, reverse complement...)", "trtools_dumpstr": "DumpSTR filters VCF files with TR genotypes, performing call-level and locus-level filtering, and outputs a fi", "expansionhunterdenovo_profile": "Compute genome-wide STR profile", "strdust": "Tandem repeat genotyper for long reads"}}, "target": "trtools_dumpstr", "target_idx": 2}
{"id": "subworkflow_pkg_bam_cnv_wisecondorx_1", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_CNV_WISECONDORX", "modules": ["wisecondorx/convert", "wisecondorx/predict"], "description": "A subworkflow for calling CNVs using WisecondorX"}, "question": {"type": "choice", "instructions": "How should BAM_CNV_WISECONDORX (wisecondorx/convert, wisecondorx/predict) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Use nf-core subworkflow bam_cnv_wisecondorx": null, "Local subworkflow BAM_CNV_WISECONDORX": null}}, "target": "Use nf-core subworkflow bam_cnv_wisecondorx", "target_idx": 2}
{"id": "schema_std_metaboigniter_0_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/metaboigniter", "description": "Pre-processing of mass spectrometry-based metabolomics data with quantification and identification based on MS1 and MS2 data.", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/metaboigniter?", "criteria": {"sample,bam,pbi,fail,repeat_id": null, "sample,fastq_1,fastq_2,group": null, "sample,type,level,msfile": null, "sample,fastq_1,fastq_2,genome": null}}, "target": "sample,type,level,msfile", "target_idx": 2}
{"id": "pipe_all101_imcyto_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for cytometry. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"diaproteomics": "Automated quantitative analysis of DIA proteomics mass spectrometry measurements. [data-independent-proteomics, dia-prot", "differentialabundance": "Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq  [atac-seq, chip-seq, d", "metapep": "From metagenomes to epitopes and beyond", "circdna": "Pipeline for the identification of extrachromosomal circular DNA (ecDNA) from Circle-seq, WGS, and ATAC-seq data that we", "createtaxdb": "Parallelised and automated construction of metagenomic classifier databases of different tools [database, database-build", "imcyto": "Image Mass Cytometry analysis pipeline [cytometry, image-analysis, image-processing]", "mag": "Assembly and binning of metagenomes [annotation, assembly, binning]", "genomeqc": "Compare the quality of multiple genomes, along with their annotations. [genome-assembly-evaluation, genomics, phylogenet"}}, "target": "imcyto", "target_idx": 5}
{"id": "qc_adapt_qc_aggregate_1_22", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Keep MultiQC": null, "Swap for NanoPlot": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "resource_bcftools_query_2", "category": "resource_profiling", "state": {"process": "BCFTOOLS_QUERY", "tool": "bcftools/query", "description": "Extracts fields from VCF or BCF files and outputs them in user-defined format."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_QUERY (Extracts fields from VCF or BCF files and outputs them in user-defined format.) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_genin2_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Genin2 is a lightining-fast bioinformatic tool to predict genotypes for H5 viruses belonging to the European clade 2.3.4.4b. (tools: genin2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biscuit_bsconv": null, "arcashla_extract": null, "alignoth": null, "gatk4_genotypegvcfs": null, "genin2": null}}, "target": "genin2", "target_idx": 4}
{"id": "resource_atlasgeneannotationmanipulation_gtf2featureannotation_5", "category": "resource_profiling", "state": {"process": "ATLASGENEANNOTATIONMANIPULATION_GTF2FEATUREANNOTATION", "tool": "atlasgeneannotationmanipulation/gtf2featureannotation", "description": "Generate tables of feature metadata from GTF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ATLASGENEANNOTATIONMANIPULATION_GTF2FEATUREANNOTATION (Generate tables of feature metadata from GTF files) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "field_constraint_status_2_5", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'status' (Tissue status for somatic cancer workflows) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'status' validated?", "criteria": {"format: file-path": null, "enum: [auto, forward, reverse]": null, "enum: [0, 1] (0=normal, 1=tumor)": null, "pattern: ^[A-Z]+$": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 2}
{"id": "qc_adapt_ffpe_wes_2_42", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "resource_affy_justrma_5", "category": "resource_profiling", "state": {"process": "AFFY_JUSTRMA", "tool": "affy/justrma", "description": "Read CEL files into an ExpressionSet and generate a matrix"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AFFY_JUSTRMA (Read CEL files into an ExpressionSet and generate a matrix) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_fasta_build_add_kraken2_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: KRAKEN2 build custom database subworkflow (tools: fasta_build_add_kraken2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"binette": null, "dysgu/run": null, "biomformat/convert": null, "kmcp/compute": null, "fasta_build_add_kraken2": null}}, "target": "fasta_build_add_kraken2", "target_idx": 4}
{"id": "qc_adapt_pacbio_hifi_0_9", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "qc_adapt_ont_ultra_long_0_5", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "qc_adapt_pacbio_hifi_1_30", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "resource_agat_spfilterfeaturefromkilllist_3", "category": "resource_profiling", "state": {"process": "AGAT_SPFILTERFEATUREFROMKILLLIST", "tool": "agat/spfilterfeaturefromkilllist", "description": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID.\nIf the feature has an ID (case insensitive) listed among the kill list it will be removed. /!\\ Removing a level1\nor level2 feature will automatically remove all linked subfeatures, and removing all children of a feature will\nautomatically remove this feature too."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SPFILTERFEATUREFROMKILLLIST (The script aims to remove features based on a kill list. The default behaviour i) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_bcftools_pluginfixploidy_2", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINFIXPLOIDY", "tool": "bcftools/pluginfixploidy", "description": "The fixploidy plugin fixes ploidy in genotype fields according to specified ploidy rules, sample sex assignments, or a forced ploidy value. For example, haploid genotypes can be converted to diploid genotypes."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINFIXPLOIDY (The fixploidy plugin fixes ploidy in genotype fields according to specified ploi) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_bam_impute_quilt2_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Impute low-coverage BAM or CRAM inputs with QUILT2 and ligate chunked outputs per chromosome.\n\"regionout\", \"regionoutPadded\", \"regionSize\" keys will be added to the meta map to distinguish\nthe different files before ligation and therefore should not be used. (tools: bam_impute_quilt2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hifitrimmer/trim": "Run hifi-trimmer trim to filter and trim adapter-hit regions from PacBio HiFi reads.\nSupports BAM/CRAM/FASTA/F", "atlas/splitmerge": "split single end read groups by length and merge paired end reads", "gatk4/samtofastq": "Converts BAM/SAM file to FastQ format", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "bam_impute_quilt2": "Impute low-coverage BAM or CRAM inputs with QUILT2 and ligate chunked outputs per chromosome.\n\"regionout\", \"re"}}, "target": "bam_impute_quilt2", "target_idx": 4}
{"id": "mod_sentieon_varcal_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module for Sentieons VarCal. The VarCal algorithm calculates the Variant Quality Score Recalibration (VQSR).\nVarCal builds a recalibration model for scoring variant quality.\nhttps://support.sentieon.com/manual/usages/general/#varcal-algorithm (tools: sentieon)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"sentieon_datametrics": "Collects multiple quality metrics from a bam file", "vcfpgloader_load": "High-performance VCF to PostgreSQL loader using asyncpg for bulk variant ingestion", "crabz_decompress": "Decompress files with crabz", "sentieon_coveragemetrics": "Accelerated implementation of the GATK DepthOfCoverage tool.", "sentieon_varcal": "Module for Sentieons VarCal. The VarCal algorithm calculates the Variant Quality Score Recalibration (VQSR).\nV"}}, "target": "sentieon_varcal", "target_idx": 4}
{"id": "pipe_all101_scnanoseq_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics. Topics: 10xgenomics, long-read-sequencing, nanopore, rna-seq, rnaseq, scrna-seq. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"scnanoseq": null, "crisprseq": null, "atacseq": null, "pacvar": null, "demo": null}}, "target": "scnanoseq", "target_idx": 0}
{"id": "noul_deprecated_dsl1_set_keyword_6", "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": "schema_std_seqinspector_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/seqinspector", "assay": "seqinspector pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/seqinspector (Dedicated QC-only pipeline for sequencing data. The pipeline)?", "criteria": {"ID,Sample,Condition,ReplicateFileName,Fasta": null, "gene_name,alignment,tree,suite,tool": null, "sample,fastq_1,fastq_2,rundir,tags": null, "sample,fastq_1,fastq_2,bam,cram": null}}, "target": "sample,fastq_1,fastq_2,rundir,tags", "target_idx": 2}
{"id": "mod_samtools_fixmate_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Samtools fixmate is a tool that can fill in information (insert size, cigar, mapq) about paired end reads onto the corresponding other read. Also has options to remove secondary/unmapped alignments and recalculate whether reads are proper pairs. (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/convertspgff2gtf": null, "rustqc": null, "pridepy/downloadfile": null, "samtools/bam2fq": null, "samtools/fixmate": null}}, "target": "samtools/fixmate", "target_idx": 4}
{"id": "qc_adapt_ffpe_wes_2_28", "category": "qc_read_adaptation", "state": {"assay": "Degraded FFPE exome capture sequencing on Illumina", "tool": "FastQC", "read_type": "short_reads_100bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Degraded FFPE exome capture sequencing on Illumina (short_reads_100bp).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_shigatyper_1", "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", "ariba_run": "Query input FASTQs against Ariba formatted databases", "art_illumina": "Simulation tool to generate synthetic Illumina next-generation sequencing reads", "bamutil_trimbam": "trims the end of reads in a SAM/BAM file, changing read ends to ‘N’ and quality to ‘!’, or by soft clipping", "picard_crosscheckfingerprints": "Checks that all data in the set of input files appear to come from the same individual"}}, "target": "shigatyper", "target_idx": 0}
{"id": "resource_bbmap_sendsketch_3", "category": "resource_profiling", "state": {"process": "BBMAP_SENDSKETCH", "tool": "bbmap/sendsketch", "description": "Compares query sketches to reference sketches hosted on a remote server via the Internet."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_SENDSKETCH (Compares query sketches to reference sketches hosted on a remote server via the ) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "samplesheet_arch_spatial_visium_1_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": "Which columns should the samplesheet have for 10x Visium spatial transcriptomics with histology image?", "criteria": {"sample,image": null, "sample,fastq_1,fastq_2": 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": "schema_std_crisprseq_1_1", "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": {"ID,Sample,Condition,ReplicateFileName,Fasta": null, "sample,fastq_1,fastq_2,condition,reference": null, "sample_id,bam,vcf,library_id,lane": null, "sample,fastq_1,fastq_2,strandedness,condition": null}}, "target": "sample,fastq_1,fastq_2,condition,reference", "target_idx": 1}
{"id": "mod_caalm_downloadmodels_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Downloads the CAALM model weights from HuggingFace Hub (lczong/CAALM) into a\nlocal models/ directory. The downloaded directory is used as input to the\nCAALM_CAALM annotation module for CAZyme prediction. (tools: huggingface_hub)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rundbcan_database": "command from run_dbcan to prepare the database for dbCAN annotation.", "caalm_downloadmodels": "Downloads the CAALM model weights from HuggingFace Hub (lczong/CAALM) into a\nlocal models/ directory. The down", "bcftools_annotate": "Add or remove annotations.", "rundbcan_easysubstrate": "Substrate annotation module for the dbcan pipeline. This module is used to annotate carbohydrate-active enzyme", "deepvariant_rundeepvariant": "DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generat"}}, "target": "caalm_downloadmodels", "target_idx": 1}
{"id": "intent_ask_question_16", "category": "intent_routing", "state": "Classify this user request: \"How does the .mix() operator differ from .combine() in Nextflow?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules"}}, "target": "ask_question", "target_idx": 3}
{"id": "qc_adapt_pe_illumina_fastqc_2_22", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Standard Paired-end Illumina RNA-seq (short_reads_150bp).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "resource_autocycler_subsample_5", "category": "resource_profiling", "state": {"process": "AUTOCYCLER_SUBSAMPLE", "tool": "autocycler/subsample", "description": "Downsample long-read sequencing data to the requested coverage using Autocycler."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AUTOCYCLER_SUBSAMPLE (Downsample long-read sequencing data to the requested coverage using Autocycler.) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "noul_confusing_combine_with_mix_semantics_8", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The operator `.combine()` performs the same operation as `.mix()` without cartesian product semantics.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_rare_disease_trio_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/raredisease", "assay_type": "Trio exome/genome sequencing (Proband, Mother, Father)", "data_format": "Paired-end FASTQs with pedigree relationships and affected status"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"family_id,sample,fastq_1,fastq_2": null, "sample,bam,bai": null, "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null}}, "target": "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2", "target_idx": 2}
{"id": "noul_deprecated_file_output_syntax_11", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Declaring `output: file('*.bam')` is the modern DSL2 syntax rather than `path('*.bam')`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "samplesheet_arch_faire_seq_chromatin_6_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 are standard for FAIRE-seq / DNAse-seq open chromatin profiling input samplesheet?", "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": "noul_default_empty_channel_behavior_24", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `Channel.fromPath('data/*.fq')` emits an error if no files match the wildcard pattern by default.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "mod_amps_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Post-processing script of the MaltExtract component of the HOPS package (tools: amps)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amps": null, "ampcombi": null, "gatk4/svannotate": null, "lissero": null, "ampcombi2/cluster": null}}, "target": "amps", "target_idx": 0}
{"id": "mod_sequenzautils_gcwiggle_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sequenza-utils gc_wiggle computes the GC percentage across the sequences, and returns a file in the UCSC wiggle format, given a fasta file and a window size. (tools: sequenzautils)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bbmap_filterbyname": "Filter out sequences by sequence header name(s)", "ascat": "copy number profiles of tumour cells.", "sequenzautils_gcwiggle": "Sequenza-utils gc_wiggle computes the GC percentage across the sequences, and returns a file in the UCSC wiggl", "cnvkit_batch": "Copy number variant detection from high-throughput sequencing data", "doubletdetection": "Doublet detection in single-cell RNA-seq data"}}, "target": "sequenzautils_gcwiggle", "target_idx": 2}
{"id": "mod_simpleaf_quant_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: simpleaf is a program to simplify and customize the running and configuration of single-cell processing with alevin-fry. (tools: simpleaf)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"diann": "Generic DIA-NN module for running any DIA-NN operation including in-silico library generation, preliminary ana", "sageproteomics/sage": "sage is a search software for proteomics data", "simpleaf/quant": "simpleaf is a program to simplify and customize the running and configuration of single-cell processing with a", "oarfish/alignmentprojectionmode": "oarfish is a program for quantifying transcript-level expression from long-read sequencing technologies. Proje", "bigslice/bigslice": "A scalable tool for large-scale analysis of Biosynthetic Gene Clusters (BGCs).\nIt takes genome regions in GenB"}}, "target": "simpleaf/quant", "target_idx": 2}
{"id": "mod_mmseqs_linclust_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Cluster sequences in linear time using MMSeqs2 linclust. (tools: mmseqs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"msisensorpro/baseline": "MSIsensor-pro/baseline builds a baseline microsatellite file from a panel of normal samples, for use with msis", "mmseqs/easycluster": "Cluster sequences using MMSeqs2 easy cluster.", "mmseqs/createindex": "Creates sequence index for mmseqs database", "regenie/runl1": "Finish REGENIE step 1 from split level-0 prediction files", "mmseqs/linclust": "Cluster sequences in linear time using MMSeqs2 linclust."}}, "target": "mmseqs/linclust", "target_idx": 4}
{"id": "pipe_all101_denovotranscript_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for denovo-assembly analysis? Specific context: A pipeline for de novo transcriptome assembly of paired-end short reads from bulk RNA-seq. Topics: denovo-assembly, rna-seq, transcriptome. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"cutandrun": "Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak callin", "phyloplace": "nf-core/phyloplace is a bioinformatics best-practice analysis pipeline that performs phylogenetic placement with EPA-NG.", "smrnaseq": "A small-RNA sequencing analysis pipeline [small-rna, smrna-seq]", "mcmicro": "An end-to-end processing pipeline that transforms multi-channel whole-slide images into single-cell data. [bioformats, i", "drugresponseeval": "Pipeline for testing drug response prediction models in a statistically and biologically sound way. [cell-lines, cross-v", "epitopeprediction": "A bioinformatics best-practice analysis pipeline for epitope prediction and annotation [epitope, epitope-prediction, mhc", "denovotranscript": "A pipeline for de novo transcriptome assembly of paired-end short reads from bulk RNA-seq [denovo-assembly, rna-seq, tra", "fetchngs": "Pipeline to fetch metadata and raw FastQ files from public databases [ddbj, download, ena]", "rnasplice": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis [alternative-splicing, rna, rna-seq]", "slamseq": "SLAMSeq processing and analysis pipeline [differential-expression, quantseq, slamseq]"}}, "target": "denovotranscript", "target_idx": 6}
{"id": "samplesheet_arch_cfdna_liquid_biopsy_4_2", "category": "samplesheet_schema", "state": {"assay": "Cell-free DNA (cfDNA) liquid biopsy longitudinal tracking", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Circulating tumor DNA FASTQs across patient clinical draw intervals?", "criteria": {"sample,bam": null, "sample,timepoint,fastq": null, "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": "qc_adapt_pe_illumina_fastqc_1_43", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "noul_include_modular_process_syntax_6", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `include { FASTQC } from './modules/fastqc/main'` is the correct syntax for importing a modular process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_ska_fasta_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create genome sketch using split k-mers (tools: ska)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"muscle5_super5": null, "agat_spfilterfeaturefromkilllist": null, "ska_fasta": null, "agat_spfilterbyorfsize": null, "sratools_prefetch": null}}, "target": "ska_fasta", "target_idx": 2}
{"id": "local_subworkflow_prepontreads_2_1", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPONTREADS", "modules": ["porechop", "nanoplot"], "description": "Nanopore adapter trimming and read quality visualization"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for PREPONTREADS (porechop, nanoplot).", "criteria": {"Leave them out": null, "Use nf-core subworkflow prepontreads": null, "Keep the modules in the main workflow": null, "Local subworkflow PREPONTREADS": null}}, "target": "Local subworkflow PREPONTREADS", "target_idx": 3}
{"id": "intent_ask_question_19", "category": "intent_routing", "state": "Classify this user request: \"What is the difference between path and file qualifiers in Nextflow DSL2 input blocks?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": null, "ask_question": null, "prepare_data": null, "build_pipeline": null}}, "target": "ask_question", "target_idx": 1}
{"id": "qc_adapt_ont_ultra_long_2_7", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "core_tool_fastqc_bare_2", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Quality control metric evaluation including per-base sequence quality scores, GC content distributions, and k-mer overrepresentation for raw FASTQ data.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"fastqc": null, "nanoplot": null, "falco": null, "qualimap": null, "multiqc": null}}, "target": "fastqc", "target_idx": 0}
{"id": "mod_hifitrimmer_filterbam_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run hifi_trimmer filter_bam to filter and trim adapter hits from PacBio HiFi reads (BAM/FASTA/FASTQ) using BLAST against\nadapter sequences. Primary output is filtered FASTA/FASTQ. (tools: hifi_trimmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hificnv": "Copy number variant calling from PacBio HiFi reads", "hifitrimmer/filterbam": "Run hifi_trimmer filter_bam to filter and trim adapter hits from PacBio HiFi reads (BAM/FASTA/FASTQ) using BLA", "cpc2": "Coding Potential Calculator 2", "yte": "A YAML template engine with Python expressions", "hifiadapterfilt/hifiadapterfilt": "Remove adapter sequences from PacBio HiFi (CCS) reads using BLAST-based\ndetection. Produces filtered FASTQ out"}}, "target": "hifitrimmer/filterbam", "target_idx": 1}
{"id": "qc_adapt_qc_aggregate_1_43", "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": "noul_multiple_script_sections_invalid_2", "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_vcf_annotation_pipeline_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/raredisease", "assay_type": "Downstream functional annotation of pre-called VCF files", "data_format": "BGZF-compressed VCF files with companion Tabix index files"}, "question": {"type": "choice", "instructions": "Which columns are standard for Downstream functional annotation of pre-called VCF files input samplesheet?", "criteria": {"sample,vcf,tbi": null, "sample,bam,bai": null, "sample,bed": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,vcf,tbi", "target_idx": 0}
{"id": "mod_agat_spflagshortintrons_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting the data to EBI.\n(Typical EBI error message: ********ERROR: Intron usually expected to be at least 10 nt long. Please check the accuracy) (tools: agat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tesorter": "An accurate and fast method to classify LTR-retrotransposons in plant genomes", "agat/spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th", "agat/spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "agat/spfilterfeaturefromkilllist": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID", "spaceranger/mkgtf": "Module to build a filtered GTF needed by the 10x Genomics Space Ranger tool. Uses the spaceranger mkgtf comman"}}, "target": "agat/spflagshortintrons", "target_idx": 1}
{"id": "mod_malt_run_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: MALT, an acronym for MEGAN alignment tool, is a sequence alignment and analysis tool designed for processing high-throughput sequencing data, especially in the context of metagenomics. (tools: malt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"malt/run": null, "maltextract": null, "malt/build": null, "universc": null, "molkartgarage/clahe": null}}, "target": "malt/run", "target_idx": 0}
{"id": "resource_ampcombi2_complete_4", "category": "resource_profiling", "state": {"process": "AMPCOMBI2_COMPLETE", "tool": "ampcombi2/complete", "description": "A submodule that merges all output summary tables from ampcombi/parsetables in one summary file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMPCOMBI2_COMPLETE (A submodule that merges all output summary tables from ampcombi/parsetables in o) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_agat_spstatistics_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Provides different type of statistics in text format from a GFF/GTF annotation file (tools: agat)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abacas": "Contiguate draft genome assembly", "ferrohgvs_parse": "Parse and validate HGVS variant descriptions with ferro", "agat_spstatistics": "Provides different type of statistics in text format from a GFF/GTF annotation file", "agat_convertspgff2gtf": "Converts a GFF/GTF file into a proper GTF file", "star_indexversion": "Get the minimal allowed index version from STAR"}}, "target": "agat_spstatistics", "target_idx": 2}
{"id": "mod_ffq_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A command line tool that makes it easier to find sequencing data from the SRA / GEO / ENA. (tools: ffq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pretextmap": "converts sam/bam/cram/pairs into genome contact map", "fastq_download_prefetch_fasterqdump_sratools": "Download FASTQ sequencing reads from the NCBI's Sequence Read Archive (SRA).", "pharmcat_vcfpreprocessor": "The PharmCAT VCF Preprocessor is a script that can pre-process VCF files for PharmCAT to make sure the VCF fil", "ffq": "A command line tool that makes it easier to find sequencing data from the SRA / GEO / ENA.", "geoquery_getgeo": "Retrieves GEO data from the Gene Expression Omnibus (GEO)"}}, "target": "ffq", "target_idx": 3}
{"id": "mod_pbsv_discover_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: pbsv - PacBio structural variant (SV) signature discovery tool (tools: pbsv)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"parabricks/indexgvcf": "NVIDIA Clara Parabricks GPU-accelerated gvcf indexing tool.", "igvreports": "A Python application to generate self-contained HTML reports for variant review and other genomic applications", "purgedups/splitfa": "Split fasta file by 'N's to aid in self alignment for duplicate purging", "graphtyper/vcfconcatenate": "Tools for population-scale genotyping using pangenome graphs.", "pbsv/discover": "pbsv - PacBio structural variant (SV) signature discovery tool"}}, "target": "pbsv/discover", "target_idx": 4}
{"id": "mod_ngscheckmate_ncm_1", "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": {"fastq_ngscheckmate": null, "krakentools_kreport2krona": null, "ngscheckmate_ncm": null, "scvitools_solo": null, "bam_ngscheckmate": null}}, "target": "ngscheckmate_ncm", "target_idx": 2}
{"id": "qc_adapt_targeted_amplicon_2_6", "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_singlecell_parse_splitseq_1_5", "category": "samplesheet_schema", "state": {"assay": "Parse Biosciences Split-seq combinatorial barcoding", "first_step": "FASTQC", "template": "nf-core/scrnaseq"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Parse Biosciences Split-seq combinatorial barcoding?", "criteria": {"sample,subpool,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,well,plate": null, "sample,bam": null}}, "target": "sample,subpool,fastq_1,fastq_2", "target_idx": 0}
{"id": "samplesheet_arch_rnafusion_pe_3_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/rnafusion --input samplesheet.csv (Assay: RNA gene fusion detection (Arriba, STAR-Fusion))", "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for RNA gene fusion detection (Arriba, STAR-Fusion) with entry step FASTQC.", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2,strandedness": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,strandedness", "target_idx": 1}
{"id": "samplesheet_arch_ont_direct_rna_se_1_3", "category": "samplesheet_schema", "state": {"assay": "Single-end Oxford Nanopore direct RNA", "first_step": "NANOPLOT", "inputs": "Single fastq per sample"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Single-end Oxford Nanopore direct RNA?", "criteria": {"sample,fastq_1": null, "sample,fast5": null, "sample,bam": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "schema_std_references_0_0", "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": {"patient,vcf,tbi,dataset,tumour_sample": null, "sample,nuclear_image,spot_table,membrane_image": null, "fasta,assembly,ncbi,gff,fastq": null, "vcf,fasta,genome,site,source": null}}, "target": "vcf,fasta,genome,site,source", "target_idx": 3}
{"id": "samplesheet_arch_bulk_wgs_pe_1_4", "category": "samplesheet_schema", "state": {"assay": "Standard Paired-end Whole Genome Sequencing (WGS)", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Standard Paired-end Whole Genome Sequencing (WGS)?", "criteria": {"sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "mod_gcta_makegrmpart_0", "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/calculateldscores": "Calculate LD scores with GCTA and derive GREML-LDMS SNP groups", "gcta/addgrms": "Combine multiple GRMs listed in an MGRM manifest into a single dense GRM", "cooler/cload": "Create a cooler from genomic pairs and bins", "sawfish/discover": "SV candidate discovery from PacBio HiFi data", "gcta/makegrmpart": "Compute one partition of a GCTA genetic relationship matrix"}}, "target": "gcta/makegrmpart", "target_idx": 4}
{"id": "qc_adapt_ont_ultra_long_0_12", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "qc_adapt_pe_illumina_fastqc_0_46", "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": "pipe_all101_metaboigniter_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Pre-processing of mass spectrometry-based metabolomics data with quantification and identification based on MS1 and MS2 data.. Topics: identification, mass-spectrometry, metabolomics, ms1, ms2, quantification. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"hicar": "Pipeline for HiCAR data, a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chrom", "seqsubmit": "nf-core pipeline for data submission to ENA", "callingcards": "A pipeline for processing calling cards data", "metaboigniter": "Pre-processing of mass spectrometry-based metabolomics data with quantification and identification based on MS1 and MS2 ", "epitopeprediction": "A bioinformatics best-practice analysis pipeline for epitope prediction and annotation [epitope, epitope-prediction, mhc"}}, "target": "metaboigniter", "target_idx": 3}
{"id": "mod_pbbam_pbmerge_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: The pbbam software package provides components to create, query, & edit PacBio BAM files and associated indices. These components include a core C++ library, bindings for additional languages, and command-line utilities. (tools: pbbam)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"atlas/splitmerge": "split single end read groups by length and merge paired end reads", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "arcane/filter": "Filter GTF annotations and genome sequence for alignment-free single-cell RNA-seq quantification with Arcane", "pbbam/pbmerge": "The pbbam software package provides components to create, query, & edit PacBio BAM files and associated indice", "hmmer/eslalimask": "Mask multiple sequence alignments"}}, "target": "pbbam/pbmerge", "target_idx": 3}
{"id": "mod_bam_sort_stats_samtools_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sort SAM/BAM/CRAM file (tools: bam_sort_stats_samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biobambam/bamsormadup": "Parallel sorting and duplicate marking", "bam_sort_stats_samtools": "Sort SAM/BAM/CRAM file", "duphold": "SV callers like lumpy look at split-reads and pair distances to find structural variants. This tool is a fast ", "bbmap/index": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode.", "poolsnp": "PoolSNP is a heuristic SNP caller, which uses an MPILEUP file and a reference genome in FASTA format as inputs"}}, "target": "bam_sort_stats_samtools", "target_idx": 1}
{"id": "field_constraint_strandedness_1_10", "category": "samplesheet_schema", "state": {"column": "strandedness", "purpose": "Library strandedness orientation in RNA-seq protocols"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'strandedness' (Library strandedness orientation in RNA-seq protocols).", "criteria": {"type: boolean": null, "pattern: ^[0-9]+$": null, "format: file-path": null, "enum: [auto, forward, reverse, unstranded]": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 3}
{"id": "mod_msisensorpro_pro_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: MSIsensor-pro/pro is a tool used to evaluate MSI using single (tumor) sample sequencing data (tools: msisensorpro)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"msisensorpro/msisomatic": null, "msisensorpro/scan": null, "msisensorpro/pro": null, "virusrecom": null, "pretextmap": null}}, "target": "msisensorpro/pro", "target_idx": 2}
{"id": "mod_purgedups_pbcstat_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create read depth histogram and base-level read depth for an assembly based on pacbio data (tools: purgedups)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastp": "Perform adapter/quality trimming on sequencing reads", "samtools_bedcov": "reports coverage over regions in a supplied BED file", "biobambam_bamsormadup": "Parallel sorting and duplicate marking", "purgedups_pbcstat": "Create read depth histogram and base-level read depth for an assembly based on pacbio data", "duphold": "SV callers like lumpy look at split-reads and pair distances to find structural variants. This tool is a fast "}}, "target": "purgedups_pbcstat", "target_idx": 3}
{"id": "intent_build_pipeline_5", "category": "intent_routing", "state": "Classify this user request: \"Can you generate a Nextflow DSL2 pipeline for paired-end Illumina RNA-seq with FastQC, STAR, and featureCounts?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"ask_question": null, "prepare_data": null, "build_pipeline": null, "debug_error": null}}, "target": "build_pipeline", "target_idx": 2}
{"id": "mod_svdb_build_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Build a structural variant database (tools: svdb)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fastq_align_dedup_bwameth": "Performs alignment of BS-Seq reads using bwameth or parabricks/fq2bammeth, sort and deduplicate", "snapaligner_align": "Performs fastq alignment to a fasta reference using SNAP", "svdb_build": "Build a structural variant database", "annotsv_annotsv": "Annotation and Ranking of Structural Variation", "gatk4_collectsvevidence": "Gathers paired-end and split read evidence files for use in the GATK-SV pipeline. Output files are a file cont"}}, "target": "svdb_build", "target_idx": 2}
{"id": "mod_prodigal_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Prodigal (Prokaryotic Dynamic Programming Genefinding Algorithm) is a microbial (bacterial and archaeal) gene finding program (tools: prodigal)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"traitar/run": "Traitar3 - predict microbial phenotypes from genomic sequences using protein families", "prodigal": "Prodigal (Prokaryotic Dynamic Programming Genefinding Algorithm) is a microbial (bacterial and archaeal) gene ", "nail/search": "nail search is a fast and scalable tool for searching protein sequences against protein databases", "wget": "The non-interactive network downloader", "antismash/antismash": "antiSMASH allows the rapid genome-wide identification, annotation\nand analysis of secondary metabolite biosynt"}}, "target": "prodigal", "target_idx": 1}
{"id": "mod_samtools_flagstat_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Counts the number of alignments in a BAM/CRAM/SAM file for each FLAG type (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"eido/convert": "Convert any PEP project or Nextflow samplesheet to any format", "bcftools/plotvcfstats": "Plots the output of bcftools stats", "samtools/flagstat": "Counts the number of alignments in a BAM/CRAM/SAM file for each FLAG type", "samtools/calmd": "calculates MD and NM tags", "ltrretriever/lai": "Estimates the mean LTR sequence identity in the genome. The input genome fasta should\nhave short alphanumeric "}}, "target": "samtools/flagstat", "target_idx": 2}
{"id": "noul_publishdir_directive_usage_6", "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_cpc2_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Coding Potential Calculator 2 (tools: cpc2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gridss/generateponbedpe": null, "cpc2": null, "agat/spfilterfeaturefromkilllist": null, "megahit": null, "agat/spmergeannotations": null}}, "target": "cpc2", "target_idx": 1}
{"id": "samplesheet_arch_epigenomics_hic_4_0", "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": "What samplesheet columns are expected when inputs are: Paired-end proximity ligation FASTQs with restriction enzyme digestion specification?", "criteria": {"sample,bam": null, "sample,matrix,contacts": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "field_constraint_status_2_6", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'status' (Tissue status for somatic cancer workflows) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'status' validated?", "criteria": {"enum: [auto, forward, reverse]": null, "pattern: ^[A-Z]+$": null, "format: file-path": null, "enum: [0, 1] (0=normal, 1=tumor)": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 3}
{"id": "local_subworkflow_prepontreads_2_3", "category": "subworkflow_packaging", "state": {"subworkflow": "PREPONTREADS", "modules": ["porechop", "nanoplot"], "description": "Nanopore adapter trimming and read quality visualization"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for PREPONTREADS (porechop, nanoplot).", "criteria": {"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_last_postmask_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Post-alignment masking (tools: last)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"last_mafconvert": "Converts MAF alignments in another format.", "last_postmask": "Post-alignment masking", "angsd_realsfs": "Estimate site frequency spectrum from site allele frequencies", "survivor_merge": "Compare or merge VCF files to generate a consensus or multi sample VCF files.", "last_lastal": "Aligns query sequences to target sequences indexed with lastdb"}}, "target": "last_postmask", "target_idx": 1}
{"id": "resource_blobtk_snail_1", "category": "resource_profiling", "state": {"process": "BLOBTK_SNAIL", "tool": "blobtk/snail", "description": "Creates blobtk snail plots."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLOBTK_SNAIL (Creates blobtk snail plots.) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "schema_std_bacass_2_1", "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": {"condition,type,microbiome_path,alleles,weights_path": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2,vcf": null, "ID,R1,R2,LongFastQ,Fast5": null}}, "target": "ID,R1,R2,LongFastQ,Fast5", "target_idx": 3}
{"id": "mod_graphmap2_align_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A versatile pairwise aligner for genomic and spliced nucleotide sequences (tools: graphmap2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ampcombi2_cluster": "A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete usin", "bbmap_align": "Align short or PacBio reads to a reference genome using BBMap", "graphmap2_align": "A versatile pairwise aligner for genomic and spliced nucleotide sequences", "gatk4_svannotate": "Adds predicted functional consequence, gene overlap, and noncoding element overlap annotations to SV VCF from ", "sentieon_bwaindex": "Create BWA index for reference genome"}}, "target": "graphmap2_align", "target_idx": 2}
{"id": "samplesheet_arch_taxprofiler_shotgun_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/taxprofiler --input samplesheet.csv (Assay: Multi-taxonomic profiling of complex metagenomic shotgun reads)", "question": {"type": "choice", "instructions": "Which columns are standard for Multi-taxonomic profiling of complex metagenomic shotgun reads input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,run_accession,instrument_platform,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "sample,run_accession,instrument_platform,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_crispresso2_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A software pipeline for the analysis of genome editing outcomes from deep sequencing data (tools: crispresso2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"crisprcleanr/normalize": "remove false positives of functional crispr genomics due to CNVs", "gapseq/draft": "Create draft metabolic model from pathway and transporter predictions", "vuegen": "The VueGen nf-core module is designed to automate report generation from outputs produced by other modules, su", "cellranger/multi": "Module to use Cell Ranger's pipelines to analyze sequencing data produced from various Chromium technologies, ", "crispresso2": "A software pipeline for the analysis of genome editing outcomes from deep sequencing data"}}, "target": "crispresso2", "target_idx": 4}
{"id": "qc_adapt_illumina_novaseq_1_23", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "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_pacbio_hifi_wgs_5_3", "category": "samplesheet_schema", "state": {"assay": "Long-read Pacific Biosciences HiFi sequencing", "first_step": "HIFIADAPTERFILT", "inputs": "Single HiFi BAM or FastQ"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/genomeassembler, determine the input samplesheet column structure for: Long-read Pacific Biosciences HiFi sequencing.", "criteria": {"sample,vcf": null, "sample,bam": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1": null}}, "target": "sample,fastq_1", "target_idx": 3}
{"id": "qc_adapt_pe_illumina_fastqc_1_14", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: short_reads_150bp?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_fasta_classify_catpack_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Taxonomic classification of binned MAGs and contigs using CAT/BAT (CAT_pack). (tools: fasta_classify_catpack)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fasta_classify_catpack": "Taxonomic classification of binned MAGs and contigs using CAT/BAT (CAT_pack).", "fasta_index_bismark_bwameth": "Generate index files from reference fasta for bismark and bwameth", "bracken_combinebrackenoutputs": "Combine output of metagenomic samples analyzed by bracken.", "bracken_bracken": "Re-estimate taxonomic abundance of metagenomic samples analyzed by kraken.", "rbt_vcfsplit": "A tool for splitting VCF/BCF files into N equal chunks, including BND support"}}, "target": "fasta_classify_catpack", "target_idx": 0}
{"id": "samplesheet_arch_cancer_longitudinal_2_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/oncoanalyser", "assay_type": "Longitudinal cancer monitoring across multiple timepoints", "data_format": "Serial plasma cfDNA and biopsy FASTQs across treatment intervals"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"patient,sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,timepoint,fastq": null, "patient,sample,timepoint,status,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,status,fastq_1,fastq_2", "target_idx": 3}
{"id": "resource_baysor_run_0", "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_low": null, "process_single": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_pacbio_hifi_0_2", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "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": "noul_multiple_script_sections_invalid_13", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"A process definition in Nextflow can declare multiple `script:` sections within the same process block.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "false", "target_idx": 0}
{"id": "pipe_all101_seqinspector_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Dedicated QC-only pipeline for sequencing data. The pipeline will run a (potentially large) set of QC tools and can output global and group specific Multiqc reports. The pipeline is targeting core facilities or research groups with larger sequencing throughput.. Topics: genomics, quality-control. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"cutandrun": "Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak callin", "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", "createtaxdb": "Parallelised and automated construction of metagenomic classifier databases of different tools [database, database-build", "nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]"}}, "target": "seqinspector", "target_idx": 1}
{"id": "samplesheet_arch_spatial_xenium_1_2", "category": "samplesheet_schema", "state": {"assay": "10x Xenium in situ subcellular spatial RNA transcriptomics", "first_step": "INPUT_CHECK", "inputs": "Xenium output bundle with transcripts CSV, cell polygons, and morphology images", "pipeline": "nf-core/spatialaxe"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for 10x Xenium in situ subcellular spatial RNA transcriptomics?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,transcripts_csv,morphology_focus_tif,cells_parquet": null, "sample,image": null, "sample,bam": null}}, "target": "sample,transcripts_csv,morphology_focus_tif,cells_parquet", "target_idx": 1}
{"id": "mod_unicycler_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Assembles bacterial genomes (tools: unicycler)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"utils_nfcore_pipeline": null, "agat_convertgff2bed": null, "chromograph": null, "unicycler": null, "agat_convertspgff2gtf": null}}, "target": "unicycler", "target_idx": 3}
{"id": "mod_bcftools_pluginscatter_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Split VCF by chunks or regions, creating multiple VCFs. (tools: pluginscatter)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools/pluginscatter": null, "atlas/call": null, "aardvark/compare": null, "nanomonsv/get": null, "presto/filterseq": null}}, "target": "bcftools/pluginscatter", "target_idx": 0}
{"id": "field_constraint_fastq_1_3_0", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "fastq_1", "validation_type": "file_pattern"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'fastq_1'.", "criteria": {"pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "enum: [auto, forward, reverse, unstranded]": null, "type: integer": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 1}
{"id": "samplesheet_arch_germline_lane_split_0_0", "category": "samplesheet_schema", "state": {"assay": "Multi-lane Illumina sequencing run of clinical samples", "first_step": "FASTQC", "inputs": "FASTQ files split across flowcell lanes (L001, L002) needing RG alignment", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Multi-lane Illumina sequencing run of clinical samples?", "criteria": {"patient,sample,lane,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "lane,fastq_1,fastq_2": null}}, "target": "patient,sample,lane,fastq_1,fastq_2", "target_idx": 0}
{"id": "resource_agat_spaddintrons_0", "category": "resource_profiling", "state": {"process": "AGAT_SPADDINTRONS", "tool": "agat/spaddintrons", "description": "Add intron features to gtf/gff file without intron features."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SPADDINTRONS (Add intron features to gtf/gff file without intron features.) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_minimap2_align_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A versatile pairwise aligner for genomic and spliced nucleotide sequences (tools: minimap2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"minimap2/align": "A versatile pairwise aligner for genomic and spliced nucleotide sequences", "ampcombi2/parsetables": "A submodule that parses and standardizes the results from various antimicrobial peptide identification tools.", "ampcombi2/cluster": "A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete usin", "msisensorpro/baseline": "MSIsensor-pro/baseline builds a baseline microsatellite file from a panel of normal samples, for use with msis", "umicollapse": "Deduplicate reads based on the mapping co-ordinate and the UMI attached to the read."}}, "target": "minimap2/align", "target_idx": 0}
{"id": "field_constraint_strandedness_0_9", "category": "samplesheet_schema", "state": {"field_name": "strandedness", "datatype": "categorical_enum", "description": "Library strandedness orientation in RNA-seq protocols"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'strandedness'?", "criteria": {"enum: [auto, forward, reverse, unstranded]": null, "format: file-path": null, "type: boolean": null, "pattern: ^[0-9]+$": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 0}
{"id": "qc_adapt_pe_illumina_fastqc_0_19", "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": "resource_bff_4", "category": "resource_profiling", "state": {"process": "BFF", "tool": "bff", "description": "Generating cell hashing calls from a matrix of count data."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BFF (Generating cell hashing calls from a matrix of count data.) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "qc_adapt_ont_ultra_long_2_43", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Ultra-long Oxford Nanopore genomic DNA reads (long_reads_20kb_plus).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "noul_modular_subworkflow_composition_12", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, subworkflows can be nested and composed inside parent workflow definitions.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_vsearch_dereplicate_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merge strictly identical sequences contained in filename. Identical sequences are defined as having the same length and the same string of nucleotides (case insensitive, T and U are considered the same). (tools: vsearch)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vsearch/dereplicate": "Merge strictly identical sequences contained in filename. Identical sequences are defined as having the same l", "deseq2/differential": "runs a differential expression analysis with DESeq2", "vsearch/cluster": "Cluster sequences using a single-pass, greedy centroid-based clustering algorithm.", "cellrangeratac/count": "Module to use Cell Ranger's ATAC pipelines analyze sequencing data produced from Chromium Single Cell ATAC.", "vsearch/fastqfilter": "Performs quality filtering and / or conversion of a FASTQ file to FASTA format."}}, "target": "vsearch/dereplicate", "target_idx": 0}
{"id": "pipe_all101_fastqrepair_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: A pipeline that can be used to recover corrupted FASTQ.gz files, drop or fix uncompliant reads, remove unpaired reads, and settles reads that became disordered. Topics: corruption, data-cleaning, data-recovery, fastq, fastq-corrupted, fastq-format. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"demo": null, "coproid": null, "fastqrepair": null, "multiplesequencealign": null, "drugresponseeval": null}}, "target": "fastqrepair", "target_idx": 2}
{"id": "local_subworkflow_positionsofint_1_2", "category": "subworkflow_packaging", "state": {"subworkflow": "POSITIONSOFINT", "modules": ["custom/positionsofint"], "description": "Position of interest depth extraction"}, "question": {"type": "choice", "instructions": "How should this step (custom/positionsofint) be packaged: Position of interest depth extraction?", "criteria": {"Local subworkflow POSITIONSOFINT": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow positionsofint": null, "Leave them out": null}}, "target": "Local subworkflow POSITIONSOFINT", "target_idx": 0}
{"id": "pipe_all101_isoseq_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for isoseq. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"diaproteomics": "Automated quantitative analysis of DIA proteomics mass spectrometry measurements. [data-independent-proteomics, dia-prot", "slamseq": "SLAMSeq processing and analysis pipeline [differential-expression, quantseq, slamseq]", "reportho": "nf-core pipeline for comparative analysis of ortholog predictions [ortholog]", "funcscan": "(Meta-)genome screening for functional and natural product gene sequences [amp, amr, antibiotic-resistance]", "isoseq": "Genome annotation with PacBio Iso-Seq. Takes raw subreads as input, generate Full Length Non Chemiric (FLNC) sequences a", "proteogenomicsdb": "The ProteoGenomics database generation workflow creates different protein databases for ProteoGenomics data analysis. [c", "proteinfamilies": "Generation and updating of protein families [metagenomics, protein-families]", "mhcquant": "Identify and quantify MHC eluted peptides from mass spectrometry raw data [dda, immunopeptidomics, mass-spectrometry]", "multiplesequencealign": "A pipeline to run and systematically evaluate Multiple Sequence Alignment (MSA) methods.", "pangenome": "Renders a collection of sequences into a pangenome graph. https://doi.org/10.1093/bioinformatics/btae609. [pangenome]"}}, "target": "isoseq", "target_idx": 4}
{"id": "resource_bcftools_sort_2", "category": "resource_profiling", "state": {"process": "BCFTOOLS_SORT", "tool": "bcftools/sort", "description": "Sorts VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_SORT (Sorts VCF files) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_high": null, "process_low": null}}, "target": "process_medium", "target_idx": 1}
{"id": "qc_adapt_ont_nanoplot_1_33", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_direct_rna?", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_fastdup_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: FastDup is a tool designed to locate and tag duplicate reads in a coordinate-sorted SAM or BAM file, using the same core algorithm as Picard MarkDuplicates. (tools: fastdup)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"fgumi/clip": "Clip overlapping reads in a BAM file with fgumi", "fastdup": "FastDup is a tool designed to locate and tag duplicate reads in a coordinate-sorted SAM or BAM file, using the", "evigene/tr2aacds": "Uses evigene/scripts/prot/tr2aacds.pl to filter a transcript assembly", "atlas/splitmerge": "split single end read groups by length and merge paired end reads", "hiphase": "Small and structural variant phasing tool for PacBio HiFi reads, supporting co-phasing of SNVs and SVs across "}}, "target": "fastdup", "target_idx": 1}
{"id": "samplesheet_arch_dual_rnaseq_host_pathogen_4_0", "category": "samplesheet_schema", "state": {"assay": "Dual RNA-seq simultaneous host and pathogen transcriptomics", "first_step": "FASTQC", "inputs": "Paired-end FASTQs from infected tissue undergoing dual mapping to human and pathogen", "pipeline": "nf-core/dualrnaseq"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Paired-end FASTQs from infected tissue undergoing dual mapping to human and pathogen?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2,host,pathogen": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,host,pathogen", "target_idx": 2}
{"id": "mod_snpsites_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Rapidly extracts SNPs from a multi-FASTA alignment. (tools: snpsites)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deepsomatic": "DeepSomatic is an extension of deep learning-based variant caller DeepVariant that takes aligned reads (in BAM", "snpsites": "Rapidly extracts SNPs from a multi-FASTA alignment.", "gem2/gemindexer": "Create a GEM index from a FASTA file", "vt/normalize": "normalizes variants in a VCF file", "vt/decomposeblocksub": "Decomposes biallelic block substitutions into its constituent SNPs."}}, "target": "snpsites", "target_idx": 1}
{"id": "samplesheet_arch_ampliseq_its_fungal_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/ampliseq) for Fungal ITS1/ITS2 marker gene amplicon surveillance. Input files: Demultiplexed paired-end Illumina MiSeq ITS fungal amplicon reads.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Fungal ITS1/ITS2 marker gene amplicon surveillance?", "criteria": {"sample,unite_fasta": null, "sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "noul_invalid_process_communication_via_globals_3", "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_khmer_normalizebymedian_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Module that calls normalize-by-median.py from khmer. The module can take a mix of paired end (interleaved) and single end reads. If both types are provided, only a single file with single ends is possible. (tools: khmer)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"antismash_antismashlite": null, "khmer_normalizebymedian": null, "khmer_trimlowabund": null, "khmer_uniquekmers": null, "gatk4_analyzecovariates": null}}, "target": "khmer_normalizebymedian", "target_idx": 1}
{"id": "mod_gatk4_cleansam_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Cleans the provided BAM, soft-clipping beyond-end-of-reference alignments and setting MAPQ to 0 for unmapped reads (tools: gatk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_cleansam": "Cleans the provided BAM, soft-clipping beyond-end-of-reference alignments and setting MAPQ to 0 for unmapped r", "fastqscreen_fastqscreen": "Align reads to multiple reference genomes using fastq-screen", "fastq_fetch_clean_hostile": "Downloads required reference genomes for hostile and removes host reads from short-read FASTQ sequencing files", "goatools_findenrichment": "Find enriched GO terms in a list of genes", "evigene_tr2aacds": "Uses evigene/scripts/prot/tr2aacds.pl to filter a transcript assembly"}}, "target": "gatk4_cleansam", "target_idx": 0}
{"id": "qc_adapt_targeted_amplicon_2_18", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "resource_bcftools_consensus_4", "category": "resource_profiling", "state": {"process": "BCFTOOLS_CONSENSUS", "tool": "bcftools/consensus", "description": "Compresses VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_CONSENSUS (Compresses VCF files) in conf/base.config?", "criteria": {"process_low": null, "process_single": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_cancer_tumor_only_2_4", "category": "samplesheet_schema", "state": {"assay": "Tumor-only somatic variant calling without matched normal", "first_step": "FASTQC", "inputs": "Paired-end FASTQ reads from tumor biopsy without matched normal", "pipeline": "nf-core/sarek"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,bam": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 2}
{"id": "noul_channel_collect_operator_23", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"The `.collect()` operator gathers all channel items into a single list item before passing to downstream processes.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_custom_tx2gene_0", "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": {"orthofinder": "OrthoFinder is a fast, accurate and comprehensive platform for comparative genomics.", "fasta_build_add_kraken2_bracken": "KRAKEN2 and BRACKEN build custom database subworkflow", "atlasgeneannotationmanipulation/gtf2featureannotation": "Generate tables of feature metadata from GTF files", "custom/tx2gene": "Make a transcript/gene mapping from a GTF and cross-reference with transcript quantifications.", "baysor/segfree": "Extract neighborhood composition vectors (NVCs) from a dataset."}}, "target": "custom/tx2gene", "target_idx": 3}
{"id": "resource_binette_2", "category": "resource_profiling", "state": {"process": "BINETTE", "tool": "binette", "description": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning tools."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BINETTE (A fast and accurate binning refinement tool to construct high quality MAGs from ) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_qc_aggregate_1_17", "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": "noul_dynamic_resource_allocation_5", "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_seroba_run_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Determine Streptococcus pneumoniae serotype from Illumina paired-end reads (tools: seroba)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"adapterremoval": "Trim sequencing adapters and collapse overlapping reads", "getorganelle_config": "Downloads databases needed for running getorganelle", "ariba_run": "Query input FASTQs against Ariba formatted databases", "amulety_balmpaired": "A module to create BALM paired embeddings of antibody (BCR) amino acid sequences using amulety.", "seroba_run": "Determine Streptococcus pneumoniae serotype from Illumina paired-end reads"}}, "target": "seroba_run", "target_idx": 4}
{"id": "qc_adapt_singlecell_multiqc_0_35", "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": "samplesheet_arch_riboseq_profiling_1_1", "category": "samplesheet_schema", "state": "nextflow run nf-core/riboseq --input samplesheet.csv (Assay: Ribosome profiling (Ribo-seq) footprint sequencing)", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Ribosome profiling (Ribo-seq) footprint sequencing?", "criteria": {"sample,bam": null, "sample,vcf": null, "sample,fastq_1,strandedness": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 2}
{"id": "subworkflow_pkg_fastq_fastqc_umitools_trimgalore_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_FASTQC_UMITOOLS_TRIMGALORE", "modules": ["fastqc", "umitools/extract", "trimgalore"], "description": "Read QC, UMI extraction and trimming"}, "question": {"type": "choice", "instructions": "How should FASTQ_FASTQC_UMITOOLS_TRIMGALORE (fastqc, umitools/extract, trimgalore) be structured in DSL2?", "criteria": {"Leave them out": null, "Use nf-core subworkflow fastq_fastqc_umitools_trimgalore": null, "Local subworkflow FASTQ_FASTQC_UMITOOLS_TRIMGALORE": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fastq_fastqc_umitools_trimgalore", "target_idx": 1}
{"id": "samplesheet_arch_cancer_somatic_bam_2_5", "category": "samplesheet_schema", "state": {"assay": "Somatic tumor-normal calling from pre-aligned BAM files", "first_step": "MUTECT2", "inputs": "Coordinate-sorted BAMs with index for tumor and normal samples"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"patient,sample,status,bam,bai": null, "sample,vcf": null, "sample,bam,bai": null, "patient,sample,bam": null}}, "target": "patient,sample,status,bam,bai", "target_idx": 0}
{"id": "mod_controlfreec_assesssignificance_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Add both Wilcoxon test and Kolmogorov-Smirnov test p-values to each CNV output of FREEC (tools: controlfreec/assesssignificance)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cobiontid/kmercounter": null, "controlfreec/assesssignificance": null, "cnvpytor/importreaddepth": null, "bam_impute_quilt2": null, "cnvnator/convert2vcf": null}}, "target": "controlfreec/assesssignificance", "target_idx": 1}
{"id": "resource_bcftools_isec_4", "category": "resource_profiling", "state": {"process": "BCFTOOLS_ISEC", "tool": "bcftools/isec", "description": "Apply set operations to VCF files"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_ISEC (Apply set operations to VCF files) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "local_subworkflow_checkirma_2_0", "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, "Keep the modules in the main workflow": null, "Local subworkflow CHECKIRMA": null, "Leave them out": null}}, "target": "Local subworkflow CHECKIRMA", "target_idx": 2}
{"id": "mod_genrich_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Peak-calling for ChIP-seq and ATAC-seq enrichment experiments (tools: genrich)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"chromap/chromap": "Performs preprocessing and alignment of chromatin fastq files to fasta reference files using chromap.", "sourmash/compare": "Compare many FracMinHash signatures generated by sourmash sketch.", "genrich": "Peak-calling for ChIP-seq and ATAC-seq enrichment experiments", "macs3/callpeak": "Peak calling of enriched genomic regions of ChIP-seq and ATAC-seq experiments", "clair3": "Clair3 is a germline small variant caller for long-reads"}}, "target": "genrich", "target_idx": 2}
{"id": "pipe_all101_fetchngs_5", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze Pipeline to fetch metadata and raw FastQ files from public databases. Topics: ddbj, download, ena, fastq, geo, sra. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina", "molkart": "A pipeline for processing Molecular Cartography data from Resolve Bioscience (combinatorial FISH) [fish, image-processin", "rnadnavar": "Pipeline for RNA and DNA integrated analysis for somatic mutation detection", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline [adna, ancient-dna-analysis, ancientdna]", "bacass": "Simple bacterial assembly and annotation pipeline [assembly, bacterial-genomes, denovo]", "nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]", "fetchngs": "Pipeline to fetch metadata and raw FastQ files from public databases [ddbj, download, ena]", "reportho": "nf-core pipeline for comparative analysis of ortholog predictions [ortholog]"}}, "target": "fetchngs", "target_idx": 6}
{"id": "mod_strelka_somatic_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Strelka2 is a fast and accurate small variant caller optimized for analysis of germline variation in small cohorts and somatic variation in tumor/normal sample pairs (tools: strelka)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"aardvark/compare": null, "cellrangerarc/mkfastq": null, "hmmer/hmmstat": null, "bcftools/call": null, "strelka/somatic": null}}, "target": "strelka/somatic", "target_idx": 4}
{"id": "core_tool_spades_metaspades_bare_1", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? De novo assembler specifically optimized for complex microbial metagenomic mixtures, recovering contigs across unequal coverage depths.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"megahit": null, "unicycler": null, "spades_metaspades": null, "flye": null, "canu": null}}, "target": "spades_metaspades", "target_idx": 2}
{"id": "mod_viennarna_rnacofold_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: calculate secondary structures of two RNAs with dimerization (tools: viennarna)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cellranger_mkvdjref": "Module to build the VDJ reference needed by the 10x Genomics Cell Ranger tool. Uses the cellranger mkvdjref co", "viennarna_rnacofold": "calculate secondary structures of two RNAs with dimerization", "circexplorer2_annotate": "Annotate circRNAs detected in the output from CIRCexplorer2 parse", "fusioncatcher_build": "Build references for fusioncatcher", "opt_stat": "stat summarizes opt binding predictions"}}, "target": "viennarna_rnacofold", "target_idx": 1}
{"id": "noul_modifying_channel_meta_inside_bash_script_block_14", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"You can modify the properties of a channel's `meta` map directly inside the process `script:` section using Groovy syntax.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "resource_abra2_5", "category": "resource_profiling", "state": {"process": "ABRA2", "tool": "abra2", "description": "Assembly Based ReAligner for next-generation sequencing data"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ABRA2 (Assembly Based ReAligner for next-generation sequencing data) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "field_constraint_strandedness_0_4", "category": "samplesheet_schema", "state": {"field_name": "strandedness", "datatype": "categorical_enum", "description": "Library strandedness orientation in RNA-seq protocols"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'strandedness'?", "criteria": {"type: boolean": null, "pattern: ^[0-9]+$": null, "format: file-path": null, "enum: [auto, forward, reverse, unstranded]": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 3}
{"id": "mod_genomad_download_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Download geNomad databases and related files (tools: genomad)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amps": "Post-processing script of the MaltExtract component of the HOPS package", "binette": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning", "genomad_download": "Download geNomad databases and related files", "biobambam_bammerge": "Merge a list of sorted bam files", "phenoimager2mc": "Formatting PhenoImager TIFF output files into stacked and normalized OME-TIFF files per cycle, compatible as A"}}, "target": "genomad_download", "target_idx": 2}
{"id": "qc_adapt_ffpe_wes_1_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": "How should QC step FastQC be configured given sequencing characteristics: short_reads_100bp?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_gatk4_variantrecalibrator_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Build a recalibration model to score variant quality for filtering purposes.\nIt is highly recommended to follow GATK best practices when using this module,\nthe gaussian mixture model requires a large number of samples to be used for the\ntool to produce optimal results. For example, 30 samples for exome data. For more details see\nhttps://gatk.broadinstitute.org/hc/en-us/articles/4402736812443-Which-training-sets-arguments-should-I-use-for-running-VQSR- (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tmb_pytmb": "This module calculates Tumor Mutational Burden (TMB) scores from VCF files using the pyTMB tool.", "gatk4_variantrecalibrator": "Build a recalibration model to score variant quality for filtering purposes.\nIt is highly recommended to follo", "mmseqs_createdb": "Create an MMseqs database from an existing FASTA/Q file", "gatk4_asereadcounter": "Calculates the allele-specific read counts for allele-specific expression analysis of RNAseq data", "gatk4_annotateintervals": "Annotates intervals with GC content, mappability, and segmental-duplication content"}}, "target": "gatk4_variantrecalibrator", "target_idx": 1}
{"id": "qc_adapt_pacbio_hifi_2_41", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "resource_ampcombi2_cluster_1", "category": "resource_profiling", "state": {"process": "AMPCOMBI2_CLUSTER", "tool": "ampcombi2/cluster", "description": "A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete using MMseqs2 cluster."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMPCOMBI2_CLUSTER (A submodule that clusters the merged AMP hits generated from ampcombi2/parsetabl) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_bamutil_trimbam_1", "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_correct": "Correct UMIs in a BAM file to a fixed set of known UMIs with fgumi", "ascat": "copy number profiles of tumour cells.", "bamaligncleaner": "removes unused references from header of sorted BAM/CRAM files.", "bamutil_trimbam": "trims the end of reads in a SAM/BAM file, changing read ends to ‘N’ and quality to ‘!’, or by soft clipping", "diamond_makedb": "Builds a DIAMOND database"}}, "target": "bamutil_trimbam", "target_idx": 3}
{"id": "mod_metaphlan_metaphlan_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: metaphlan)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"metaphlan_metaphlan": "MetaPhlAn is a tool for profiling the composition of microbial communities from metagenomic shotgun sequencing", "argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD).", "subread_featurecounts": "Count reads that map to genomic features", "binette": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning", "ngsbits_bedcoverage": "Annotates a BED file with the average coverage of the regions from one or several BAM/CRAM file(s)."}}, "target": "metaphlan_metaphlan", "target_idx": 0}
{"id": "field_constraint_sample_2_6", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'sample' (Sample identifier across all nf-core pipelines) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'sample' validated?", "criteria": {"type: integer": null, "enum: [0, 1]": null, "pattern: ^\\S+$ (no whitespace, unique)": null, "format: file-path": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 2}
{"id": "mod_fastplong_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform adapter/quality trimming and QC on long sequencing reads (ONT, PacBio, etc.) (tools: fastplong)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"chopper": "Filter and trim long read data.", "quantify_pseudo_alignment": "Perform quantification with Salmon or Kallisto to produce count tables and SummarizedExperiment objects", "chromap_chromap": "Performs preprocessing and alignment of chromatin fastq files to fasta reference files using chromap.", "fastplong": "Perform adapter/quality trimming and QC on long sequencing reads (ONT, PacBio, etc.)", "fastx_collapser": "Collapses identical sequences in a FASTQ/A file into a single sequence (while maintaining reads counts)"}}, "target": "fastplong", "target_idx": 3}
{"id": "samplesheet_arch_rare_disease_trio_1_4", "category": "samplesheet_schema", "state": {"assay": "Trio exome/genome sequencing (Proband, Mother, Father)", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Trio exome/genome sequencing (Proband, Mother, Father)?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,bam,bai": null, "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2": null}}, "target": "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2", "target_idx": 3}
{"id": "field_constraint_fastq_2_1_0", "category": "samplesheet_schema", "state": {"column": "fastq_2", "purpose": "Path to read 2 FASTQ file for paired-end sequencing"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'fastq_2' (Path to read 2 FASTQ file for paired-end sequencing).", "criteria": {"type: required string": null, "pattern: ^\\S+\\.bam$": null, "enum: [0, 1]": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$ (optional for single-end)", "target_idx": 3}
{"id": "samplesheet_arch_spatial_visium_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/spatialaxe", "assay_type": "10x Visium spatial transcriptomics with histology image", "data_format": "Spatial cDNA FASTQs paired with high-resolution brightfield tissue image and slide coordinates"}, "question": {"type": "choice", "instructions": "Which columns are standard for 10x Visium spatial transcriptomics with histology image input samplesheet?", "criteria": {"sample,bam": null, "sample,fastq_1,image": null, "sample,fastq_1,fastq_2,image,slide,area": null, "sample,image": null}}, "target": "sample,fastq_1,fastq_2,image,slide,area", "target_idx": 2}
{"id": "samplesheet_arch_singlecell_parse_splitseq_1_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": "Which columns should the samplesheet have for Parse Biosciences Split-seq combinatorial barcoding?", "criteria": {"sample,bam": null, "sample,fastq_1": 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": "field_constraint_fastq_1_1_10", "category": "samplesheet_schema", "state": {"column": "fastq_1", "purpose": "Path to read 1 FASTQ file (gzipped or uncompressed)"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'fastq_1' (Path to read 1 FASTQ file (gzipped or uncompressed)).", "criteria": {"pattern: ^\\S+\\.bam$": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "enum: [auto, forward, reverse, unstranded]": null, "type: integer": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 1}
{"id": "samplesheet_arch_cancer_somatic_tn_2_0", "category": "samplesheet_schema", "state": {"technology": "Cancer Genomics", "workflow_entry": "BWA_MEM", "library_inputs": "Paired-end FASTQs for patient tumor and germline normal tissue"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 0}
{"id": "field_constraint_bam_2_7", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'bam' (Path to aligned binary sequence alignment (BAM) file) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'bam' validated?", "criteria": {"pattern: ^\\S+\\.bam$": null, "format: uri": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.vcf(\\.gz)?$": null}}, "target": "pattern: ^\\S+\\.bam$", "target_idx": 0}
{"id": "subworkflow_pkg_quantify_pseudo_alignment_2", "category": "subworkflow_packaging", "state": {"subworkflow": "QUANTIFY_PSEUDO_ALIGNMENT", "modules": ["kallisto/quant", "quant_tximport_summarizedexperiment", "salmon/quant"], "description": "Perform quantification with Salmon or Kallisto to produce count tables and SummarizedExperiment objects"}, "question": {"type": "choice", "instructions": "How should QUANTIFY_PSEUDO_ALIGNMENT (kallisto/quant, quant_tximport_summarizedexperiment, salmon/quant) be structured in DSL2?", "criteria": {"Use nf-core subworkflow quantify_pseudo_alignment": null, "Leave them out": null, "Local subworkflow QUANTIFY_PSEUDO_ALIGNMENT": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow quantify_pseudo_alignment", "target_idx": 0}
{"id": "pipe_all101_hic_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for chromosome-conformation-capture analysis? Specific context: Analysis of Chromosome Conformation Capture data (Hi-C). Topics: chromosome-conformation-capture, hi-c. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"kmermaid": " k-mer similarity analysis pipeline [k-mer, kmer, kmer-counting]", "nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]", "mhcquant": "Identify and quantify MHC eluted peptides from mass spectrometry raw data [dda, immunopeptidomics, mass-spectrometry]", "oncoanalyser": "A comprehensive cancer DNA/RNA analysis and reporting pipeline [cancer, clinical, ctdna]", "hic": "Analysis of Chromosome Conformation Capture data (Hi-C) [chromosome-conformation-capture, hi-c]"}}, "target": "hic", "target_idx": 4}
{"id": "mod_nonpareil_nonpareil_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculate metagenome redundancy curve from FASTQ files (tools: nonpareil)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bracken/combinebrackenoutputs": "Combine output of metagenomic samples analyzed by bracken.", "hmmcopy/mapcounter": "mapCounter function from HMMcopy utilities, used to generate mappability in non-overlapping windows from a big", "biomformat/convert": "Convert biom table to different format.\nConversion between text tab-delimited, BIOM-v1 (JSON), and BIOM-v2 (HD", "nonpareil/nonpareil": "Calculate metagenome redundancy curve from FASTQ files", "gatk/realignertargetcreator": "Generates a list of locations that should be considered for local realignment prior genotyping."}}, "target": "nonpareil/nonpareil", "target_idx": 3}
{"id": "qc_adapt_pacbio_hifi_1_16", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "samplesheet_arch_ont_demux_barcodes_5_4", "category": "samplesheet_schema", "state": {"assay": "Multiplexed Oxford Nanopore run with barcode demultiplexing", "first_step": "NANOPLOT"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/nanoseq, determine the input samplesheet column structure for: Multiplexed Oxford Nanopore run with barcode demultiplexing.", "criteria": {"sample,bam": null, "sample,barcode,flowcell,kit,fastq": null, "sample,fastq_1": null, "sample,barcode": null}}, "target": "sample,barcode,flowcell,kit,fastq", "target_idx": 1}
{"id": "core_tool_featurecounts_described_2", "category": "tool_selection", "state": "Which bioinformatics tool or module is best suited for this task? Assign and quantify mapped reads to genomic features such as exons, genes, and promoter annotations from sorted BAM files.", "question": {"type": "choice", "instructions": "Select the appropriate bioinformatics tool or module for the specified task.", "criteria": {"featurecounts": "Assign sequence reads to genomic features (genes, exons, promoters)", "htseq": "High-throughput sequencing analysis", "stringtie": "Transcript assembly", "kallisto": "RNA quantification", "salmon": "Transcript quantifier"}}, "target": "featurecounts", "target_idx": 0}
{"id": "samplesheet_arch_ont_direct_rna_se_4_0", "category": "samplesheet_schema", "state": {"assay": "Single-end Oxford Nanopore direct RNA", "first_step": "NANOPLOT", "inputs": "Single fastq per sample", "pipeline": "nf-core/nanoseq"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected when inputs are: Single fastq per sample?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,fastq_1", "target_idx": 2}
{"id": "schema_std_createpanelrefs_2_0", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/createpanelrefs. Description: Generate Panel of Normals, models or other similar references from lots of samples.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/createpanelrefs.", "criteria": {"sample,bam,bai,cram,crai": null, "ID,R1,R2,LongFastQ,Fast5": null, "sample_id,group_id,subject_id,sample_type,sequence_type": null, "id,test_vcf,test_regions,caller,subsample": null}}, "target": "sample,bam,bai,cram,crai", "target_idx": 0}
{"id": "qc_adapt_bulk_multiqc_1_1", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep FastQC": null, "Drop MultiQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 3}
{"id": "mod_vcf_filter_bcftools_ensemblvep_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filter VCF file with bcftools and filter_vep (tools: vcf_filter_bcftools_ensemblvep)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"parabricks/deepvariant": "NVIDIA Clara Parabricks GPU-accelerated germline variant calling, replicating deepvariant.", "agat/spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas", "bamcmp": "Bamcmp (Bam Compare) is a tool for assigning reads between a primary genome and a contamination genome. For in", "vcf_filter_bcftools_ensemblvep": "Filter VCF file with bcftools and filter_vep", "deepvariant/postprocessvariants": "DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generat"}}, "target": "vcf_filter_bcftools_ensemblvep", "target_idx": 3}
{"id": "resource_blobtk_depth_3", "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_single": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "resource_bcftools_annotate_2", "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_low": null, "process_single": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_targeted_amplicon_1_4", "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_segemehl_align_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A multi-split mapping algorithm for circular RNA, splicing, trans-splicing and fusion detection (tools: segemehl)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bwa/sampe": null, "amps": null, "segemehl/align": null, "bwa/mem": null, "ismapper": null}}, "target": "segemehl/align", "target_idx": 2}
{"id": "mod_openms_idripper_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Split a merged identification file into their originating identification files (tools: openms)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom_multiqccustombiotype": null, "openms_idripper": null, "atlas_splitmerge": null, "mobsuite_recon": null, "bcftools_pluginsplit": null}}, "target": "openms_idripper", "target_idx": 1}
{"id": "noul_named_process_output_emits_5", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Nextflow DSL2 supports multi-channel emission from processes using named emit blocks: `path '*.bam', emit: bam`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "mod_gatk4_composestrtablefile_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: This tool looks for low-complexity STR sequences along the reference that are later used to estimate the Dragstr model during single sample auto calibration CalibrateDragstrModel. (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rgi_main": "Predict antibiotic resistance from protein or nucleotide data", "gatk4_composestrtablefile": "This tool looks for low-complexity STR sequences along the reference that are later used to estimate the Drags", "snpsites": "Rapidly extracts SNPs from a multi-FASTA alignment.", "gatk4_analyzecovariates": "Evaluate and compare base quality score recalibration (BQSR) tables", "gatk4_baserecalibrator": "Generate recalibration table for Base Quality Score Recalibration (BQSR)"}}, "target": "gatk4_composestrtablefile", "target_idx": 1}
{"id": "samplesheet_arch_atacseq_replicates_6_5", "category": "samplesheet_schema", "state": {"assay": "ATAC-seq chromatin accessibility with biological replicates", "first_step": "FASTQC", "inputs": "Paired-end Tn5 transposed FASTQs across conditions and replicates"}, "question": {"type": "choice", "instructions": "Which columns are standard for ATAC-seq chromatin accessibility with biological replicates input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,replicate": null, "sample,bed": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,replicate", "target_idx": 1}
{"id": "field_constraint_expected_cells_0_11", "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, "pattern: ^\\S+\\.csv$": null, "enum: [auto, single, paired]": null, "format: file-path": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 0}
{"id": "noul_undeclared_process_file_inputs_22", "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": "pipe_all101_methylong_0", "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": {"metatdenovo": null, "fastquorum": null, "methylong": null, "proteinfold": null, "proteinfamilies": null, "diaproteomics": null, "variantbenchmarking": null, "demultiplex": null}}, "target": "methylong", "target_idx": 2}
{"id": "mod_quarto_prerender_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Pre-render a Quarto document to markdown, including parametrization (tools: quarto)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"jupyternotebook": "Render jupyter (or jupytext) notebooks to HTML reports. Supports parametrization\nthrough papermill.", "odgi/draw": "Draw previously-determined 2D layouts of the graph with diverse annotations.", "quarto/prerender": "Pre-render a Quarto document to markdown, including parametrization", "amrfinderplus/run": "Identify antimicrobial resistance in gene or protein sequences", "pypolca/run": "Short read polisher for long read assemblies"}}, "target": "quarto/prerender", "target_idx": 2}
{"id": "mod_csvtk_split_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Splits CSV/TSV into multiple files according to column values (tools: csvtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bamtools_split": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files.", "skani_search": "Memory-efficient ANI database queries with skani.", "csvtk_split": "Splits CSV/TSV into multiple files according to column values", "amulety_translate": "A module to translate BCR and TCR nucleotide sequences into amino acid sequences using amulety and igblast.", "dshbio_splitbed": "Split features in gzipped BED format"}}, "target": "csvtk_split", "target_idx": 2}
{"id": "pipe_all101_lsmquant_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for 3dunet. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"hlatyping": "Precision HLA typing from next-generation sequencing data [dna, hla, hla-typing]", "phaseimpute": "A bioinformatics pipeline to phase and impute genetic data [genomics, genotype, imputation]", "cutandrun": "Analysis pipeline for CUT&RUN and CUT&TAG experiments that includes QC, support for spike-ins, IgG controls, peak callin", "seqinspector": "Dedicated QC-only pipeline for sequencing data. The pipeline will run a (potentially large) set of QC tools and can outp", "metapep": "From metagenomes to epitopes and beyond", "dualrnaseq": "Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous", "lsmquant": "A pipeline for processing and analysis of light-sheet microscopy images. [3dunet, image-analysis, image-processing]", "proteinannotator": "Generation of sequence-level annotations for amino acid sequences [annotation, proteomics]"}}, "target": "lsmquant", "target_idx": 6}
{"id": "resource_agat_convertgff2bed_2", "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_high": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_svim_alignment_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Structural variant detection from long-read sequencing alignments using SVIM. (tools: svim)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"leviosam2/lift": null, "annotsv/annotsv": null, "svim/alignment": null, "caddsv/get": null, "sentieon/applyvarcal": null}}, "target": "svim/alignment", "target_idx": 2}
{"id": "noul_module_metadata_propagation_8", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, modules must accept and pass sample metadata tuples `[ val(meta), path(reads) ]` through channels.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_pe_illumina_fastqc_2_27", "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": "samplesheet_arch_pacbio_hifi_unaligned_bam_5_2", "category": "samplesheet_schema", "state": {"assay": "PacBio HiFi unaligned BAM variant calling", "first_step": "PBMM2_ALIGN", "inputs": "Native unaligned PacBio Sequel IIe / Revio BAM containing kinetics and qualities", "pipeline": "nf-core/pacvar"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/pacvar, determine the input samplesheet column structure for: PacBio HiFi unaligned BAM variant calling.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,vcf": null, "sample,bam,bai": null}}, "target": "sample,bam", "target_idx": 1}
{"id": "mod_gfastats_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A single fast and exhaustive tool for summary statistics and simultaneous *fa*\n(fasta, fastq, gfa [.gz]) genome assembly file manipulation. (tools: gfastats)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"cellbender/merge": "Module to use CellBender to remove ambient RNA from single-cell RNA-seq data", "any2fasta": "Convert various sequence formats (GenBank, GFF, FASTQ, FASTA, CLUSTAL, Stockholm, GFA) to FASTA format. Input ", "abritamr/run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes", "stringtie/merge": "Merges the annotation gtf file and the stringtie output gtf files", "gfastats": "A single fast and exhaustive tool for summary statistics and simultaneous *fa*\n(fasta, fastq, gfa [.gz]) genom"}}, "target": "gfastats", "target_idx": 4}
{"id": "mod_bioformats2raw_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Java application to convert image file formats, including .mrxs, to an intermediate Zarr structure compatible with the OME-NGFF specification. (tools: bioformats2raw)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"salmon_index": null, "bio2zarr_vcf2zarrexplode": null, "bio2zarr_vcf2zarrconvert": null, "nonpareil_nonpareil": null, "bioformats2raw": null}}, "target": "bioformats2raw", "target_idx": 4}
{"id": "samplesheet_arch_chipseq_with_control_8_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 single-end ONT?", "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": "samplesheet_arch_cancer_somatic_tn_2_5", "category": "samplesheet_schema", "state": {"assay": "Somatic cancer variant calling with tumor-normal pairs", "first_step": "BWA_MEM", "inputs": "Paired-end FASTQs for patient tumor and germline normal tissue"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,bam": null, "patient,sample,status,fastq_1,fastq_2": null, "patient,sample,status,bam,bai": null, "sample,fastq_1": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 1}
{"id": "resource_bedtools_genomecov_2", "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_medium": null, "process_single": null, "process_high": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_coptr_map_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Maps the reads to the reference database (tools: coptr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"coptr_merge": "Merge reads that were mapped to multiple indices", "cleanifier_index": "Builds a Cuckoo filter or Cuckoo hash table index from reference sequences (FASTA/FASTQ) for fast contaminatio", "telseq": "Telseq: a software for calculating telomere length", "coptr_map": "Maps the reads to the reference database", "coptr_extract": "Computes the coverage map along the reference genome"}}, "target": "coptr_map", "target_idx": 3}
{"id": "resource_anarcii_1", "category": "resource_profiling", "state": {"process": "ANARCII", "tool": "anarcii", "description": "A language model for antigen receptor numbering"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANARCII (A language model for antigen receptor numbering) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_ont_nanoplot_0_17", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "For Direct RNA sequencing on Oxford Nanopore PromethION, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/pacvar --input samplesheet.csv (Assay: PacBio HiFi unaligned BAM variant calling)", "question": {"type": "choice", "instructions": "Which columns are standard for PacBio HiFi unaligned BAM variant calling input samplesheet?", "criteria": {"sample,bam": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null, "sample,bam,bai": null}}, "target": "sample,bam", "target_idx": 0}
{"id": "resource_atlas_call_4", "category": "resource_profiling", "state": {"process": "ATLAS_CALL", "tool": "atlas/call", "description": "generate VCF file from a BAM file using various calling methods"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ATLAS_CALL (generate VCF file from a BAM file using various calling methods) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_long": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "resource_bismark_deduplicate_4", "category": "resource_profiling", "state": {"process": "BISMARK_DEDUPLICATE", "tool": "bismark/deduplicate", "description": "Removes alignments to the same position in the genome\nfrom the Bismark mapping output."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_DEDUPLICATE (Removes alignments to the same position in the genome\nfrom the Bismark mapping o) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "samplesheet_arch_bulk_rnaseq_pe_standard_0_4", "category": "samplesheet_schema", "state": {"technology": "Bulk RNA-seq", "workflow_entry": "FASTQC", "library_inputs": "FastQ reads per sample"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Paired-end Illumina RNA-seq?", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2,group": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "noul_exit_code_137_cause_15", "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": "subworkflow_pkg_bam_variant_calling_mpileup_bcftools_3", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_VARIANT_CALLING_MPILEUP_BCFTOOLS", "modules": ["gawk", "tabix/bgzip", "bcftools/mpileup", "bcftools/merge", "bcftools/annotate", "bcftools/concat", "vcf_gather_bcftools"], "description": "Subworkflow to compute genotype likelihoods from BAM files using"}, "question": {"type": "choice", "instructions": "How should BAM_VARIANT_CALLING_MPILEUP_BCFTOOLS (gawk, tabix/bgzip, bcftools/mpileup, bcftools/merge, bcftools/annotate, bcftools/concat, vcf_gather_bcftools) be structured in DSL2?", "criteria": {"Leave them out": null, "Use nf-core subworkflow bam_variant_calling_mpileup_bcftools": null, "Local subworkflow BAM_VARIANT_CALLING_MPILEUP_BCFTOOLS": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow bam_variant_calling_mpileup_bcftools", "target_idx": 1}
{"id": "noul_channel_operator_map_10", "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_ont_ultra_long_0_25", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "For Ultra-long Oxford Nanopore genomic DNA reads, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "resource_bbmap_align_3", "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_long": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_ampcombi2_complete_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A submodule that merges all output summary tables from ampcombi/parsetables in one summary file. (tools: ampcombi2/complete)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ampcombi": "A tool to parse and summarise results from antimicrobial peptides tools and present functional classification.", "rpbp_extractmetageneprofiles": "Build per-read-length pileups of Ribo-seq read 5'-ends around annotated\nstart codons - the \"metagene profile\".", "foldmason_createdb": "Creates a database for Foldmason.", "ampcombi2_complete": "A submodule that merges all output summary tables from ampcombi/parsetables in one summary file.", "ampcombi2_parsetables": "A submodule that parses and standardizes the results from various antimicrobial peptide identification tools."}}, "target": "ampcombi2_complete", "target_idx": 3}
{"id": "mod_galah_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Cluster genome FASTA files by average nucleotide identity (tools: galah)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"lima": "lima - The PacBio Barcode Demultiplexer and Primer Remover", "deeptools/plotcorrelation": "Visualises sample correlations using a compressed matrix generated by mutlibamsummary or multibigwigsummary as", "galah": "Cluster genome FASTA files by average nucleotide identity", "agat/spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated", "agat/spfilterfeaturefromkilllist": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID"}}, "target": "galah", "target_idx": 2}
{"id": "resource_abyss_abysspe_3", "category": "resource_profiling", "state": {"process": "ABYSS_ABYSSPE", "tool": "abyss/abysspe", "description": "ABySS is a de novo sequence assembler intended for short paired-end reads and genomes of all sizes."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ABYSS_ABYSSPE (ABySS is a de novo sequence assembler intended for short paired-end reads and ge) in conf/base.config?", "criteria": {"process_low": null, "process_long": null, "process_medium": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "resource_ataqv_ataqv_1", "category": "resource_profiling", "state": {"process": "ATAQV_ATAQV", "tool": "ataqv/ataqv", "description": "ataqv function of a corresponding ataqv tool"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ATAQV_ATAQV (ataqv function of a corresponding ataqv tool) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_high": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "qc_adapt_ont_ultra_long_0_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": "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": "subworkflow_pkg_bam_docounts_contamination_angsd_1", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_DOCOUNTS_CONTAMINATION_ANGSD", "modules": ["angsd/docounts", "angsd/contamination"], "description": "Calculate contamination of the X-chromosome with ANGSD"}, "question": {"type": "choice", "instructions": "How should BAM_DOCOUNTS_CONTAMINATION_ANGSD (angsd/docounts, angsd/contamination) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow BAM_DOCOUNTS_CONTAMINATION_ANGSD": null, "Use nf-core subworkflow bam_docounts_contamination_angsd": null}}, "target": "Use nf-core subworkflow bam_docounts_contamination_angsd", "target_idx": 3}
{"id": "mod_gatk4_condensedepthevidence_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Merges adjacent DepthEvidence records (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_condensedepthevidence": null, "gatk4_applybqsr": null, "gatk4_annotateintervals": null, "diamond_linclust": null, "pairtools_restrict": null}}, "target": "gatk4_condensedepthevidence", "target_idx": 0}
{"id": "samplesheet_arch_ont_direct_rna_se_6_4", "category": "samplesheet_schema", "state": {"assay": "Single-end Oxford Nanopore direct RNA", "first_step": "NANOPLOT", "inputs": "Single fastq per sample", "pipeline": "nf-core/nanoseq"}, "question": {"type": "choice", "instructions": "Which columns are standard for Single-end Oxford Nanopore direct RNA input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "qc_adapt_pe_illumina_fastqc_0_20", "category": "qc_read_adaptation", "state": {"assay": "Standard Paired-end Illumina RNA-seq", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "For Standard Paired-end Illumina RNA-seq, what is the recommended QC default for FastQC?", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_pairtools_parse_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Find ligation junctions in .sam, make .pairs (tools: pairtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"circexplorer2_parse": null, "seqtk_cutn": null, "pairtools_parse": null, "gatk4_mergemutectstats": null, "ferrohgvs_parse": null}}, "target": "pairtools_parse", "target_idx": 2}
{"id": "field_constraint_status_2_2", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'status' (Tissue status for somatic cancer workflows) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'status' validated?", "criteria": {"format: file-path": null, "enum: [auto, forward, reverse]": null, "pattern: ^[A-Z]+$": null, "enum: [0, 1] (0=normal, 1=tumor)": null}}, "target": "enum: [0, 1] (0=normal, 1=tumor)", "target_idx": 3}
{"id": "qc_adapt_pacbio_hifi_1_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": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "qc_adapt_qc_aggregate_2_26", "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": "qc_adapt_targeted_amplicon_0_46", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "For Targeted Illumina amplicon panel, what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "mod_goleft_indexcov_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Quickly estimate coverage from a whole-genome bam or cram index. A bam index has 16KB resolution so that's what this gives, but it provides what appears to be a high-quality coverage estimate in seconds per genome. (tools: goleft)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bbmap_bbnorm": "BBNorm is designed to normalize coverage by down-sampling reads over high-depth areas of a genome, to result i", "cnvkit_coverage": "Calculate coverage in the given regions from BAM/CRAM or bedGraph files read depths.", "fastq_download_prefetch_fasterqdump_sratools": "Download FASTQ sequencing reads from the NCBI's Sequence Read Archive (SRA).", "grimer": "Generates an interactive HTML dashboard integrating taxonomy,\nannotation, and metadata to detect contamination", "goleft_indexcov": "Quickly estimate coverage from a whole-genome bam or cram index. A bam index has 16KB resolution so that's wha"}}, "target": "goleft_indexcov", "target_idx": 4}
{"id": "intent_debug_error_23", "category": "intent_routing", "state": "Classify this user request: \"ERROR ~ Error executing process > 'SAMTOOLS_SORT' (command not found, exit status 127)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": null, "build_pipeline": null, "debug_error": null, "ask_question": null}}, "target": "debug_error", "target_idx": 2}
{"id": "resource_bedtools_slop_3", "category": "resource_profiling", "state": {"process": "BEDTOOLS_SLOP", "tool": "bedtools/slop", "description": "Adds a specified number of bases in each direction (unique values may be specified for either -l or -r)"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_SLOP (Adds a specified number of bases in each direction (unique values may be specifi) in conf/base.config?", "criteria": {"process_high": null, "process_medium": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "samplesheet_arch_cancer_tumor_only_7_0", "category": "samplesheet_schema", "state": {"assay": "Tumor-only somatic variant calling without matched normal", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for tumor-normal pairs?", "criteria": {"sample,fastq_1": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "patient,normal,tumor": null}}, "target": "patient,sample,status,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_modkit_repair_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Repair the MM/ML tags on trimmed or hard-clipped ONT reads using untrimmed ONT reads. (tools: modkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bismark/methylationextractor": null, "bwamem3/mem": null, "mmseqs/createtaxdb": null, "bismark/report": null, "modkit/repair": null}}, "target": "modkit/repair", "target_idx": 4}
{"id": "samplesheet_arch_ancient_dna_eager_5_4", "category": "samplesheet_schema", "state": {"assay": "Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/eager, determine the input samplesheet column structure for: Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment.", "criteria": {"sample,bam": null, "sample,fastq_1,fastq_2": null, "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null, "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": "resource_agat_convertspgff2gtf_3", "category": "resource_profiling", "state": {"process": "AGAT_CONVERTSPGFF2GTF", "tool": "agat/convertspgff2gtf", "description": "Converts a GFF/GTF file into a proper GTF file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_CONVERTSPGFF2GTF (Converts a GFF/GTF file into a proper GTF file) in conf/base.config?", "criteria": {"process_medium": null, "process_long": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_maltextract_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Tool for evaluation of MALT results for true positives of ancient metagenomic taxonomic screening (tools: maltextract)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gtdbtk/classifywf": "GTDB-Tk is a software toolkit for assigning objective taxonomic classifications to bacterial and archaeal geno", "ganon/table": "Generate a multi-sample report file from the output of ganon report runs", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "malt/build": "MALT, an acronym for MEGAN alignment tool, is a sequence alignment and analysis tool designed for processing h", "maltextract": "Tool for evaluation of MALT results for true positives of ancient metagenomic taxonomic screening"}}, "target": "maltextract", "target_idx": 4}
{"id": "qc_adapt_bulk_multiqc_1_30", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Swap for NanoPlot": null, "Drop MultiQC": null, "Keep MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_mmseqs_createindex_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Creates sequence index for mmseqs database (tools: mmseqs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"seqtk_sample": null, "mmseqs_easycluster": null, "mmseqs_createindex": null, "refsolver_score": null, "mmseqs_cluster": null}}, "target": "mmseqs_createindex", "target_idx": 2}
{"id": "field_constraint_fastq_1_0_9", "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, "enum: [auto, forward, reverse, unstranded]": null, "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$": null, "pattern: ^\\S+\\.bam$": null}}, "target": "pattern: ^\\S+\\.f(ast)?q(\\.gz)?$", "target_idx": 2}
{"id": "qc_adapt_pe_illumina_fastqc_2_23", "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": "pipe_all101_pacvar_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Longread PacBio sequencing processing for WGS and PureTarget. Topics: alignment, long-read, pacbio, puretarget, variant-calling, wgs. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"proteogenomicsdb": null, "diaproteomics": null, "pacvar": null, "bamtofastq": null, "pixelator": null, "kmermaid": null, "stableexpression": null, "variantbenchmarking": null, "rnaseq": null, "imcyto": null}}, "target": "pacvar", "target_idx": 2}
{"id": "qc_adapt_bulk_multiqc_0_46", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For High-throughput bulk WGS multi-sample run, what is the recommended QC default for MultiQC?", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "pipe_all101_rangeland_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Pipeline for remotely sensed imagery. The pipeline processes satellite imagery alongside auxiliary data in multiple steps to arrive at a set of trend files related to land-cover changes.. Topics: earth-observation, landsat, satellite-imagery, spectral-unmixing, trend-analysis, trends. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"metatdenovo": "Assembly and annotation of metatranscriptomic or metagenomic data for prokaryotic, eukaryotic and viruses. [eukaryotes, ", "smrnaseq": "A small-RNA sequencing analysis pipeline [small-rna, smrna-seq]", "rangeland": "Pipeline for remotely sensed imagery. The pipeline processes satellite imagery alongside auxiliary data in multiple step", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "reportho": "nf-core pipeline for comparative analysis of ortholog predictions [ortholog]", "drop": "Pipeline to find aberrant events in RNA-Seq data, useful for diagnosis of rare disorders", "ribomsqc": "QC pipeline that monitors mass spectrometer performance in ribonucleoside analysis", "seqsubmit": "nf-core pipeline for data submission to ENA"}}, "target": "rangeland", "target_idx": 2}
{"id": "qc_adapt_ont_nanoplot_2_27", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "resource_bismark_genomepreparation_0", "category": "resource_profiling", "state": {"process": "BISMARK_GENOMEPREPARATION", "tool": "bismark/genomepreparation", "description": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for alignments."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_GENOMEPREPARATION (Converts a specified reference genome into two different bisulfite\nconverted ver) in conf/base.config?", "criteria": {"process_medium": null, "process_low": null, "process_single": null, "process_high": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_graphmap2_index_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A versatile pairwise aligner for genomic and spliced nucleotide sequences (tools: graphmap2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bismark/genomepreparation": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for ali", "bcftools/index": "Index VCF tools", "odgi/build": "Construct a dynamic succinct variation graph in ODGI format from a GFAv1.", "dedup": "DeDup is a tool for read deduplication in paired-end read merging (e.g. for ancient DNA experiments).", "graphmap2/index": "A versatile pairwise aligner for genomic and spliced nucleotide sequences"}}, "target": "graphmap2/index", "target_idx": 4}
{"id": "subworkflow_pkg_cache_download_ensemblvep_snpeff_3", "category": "subworkflow_packaging", "state": {"subworkflow": "CACHE_DOWNLOAD_ENSEMBLVEP_SNPEFF", "modules": ["ensemblvep/download", "snpeff/download"], "description": "downlad annotation cache for snpeff and ensemblvep"}, "question": {"type": "choice", "instructions": "How should CACHE_DOWNLOAD_ENSEMBLVEP_SNPEFF (ensemblvep/download, snpeff/download) be structured in DSL2?", "criteria": {"Local subworkflow CACHE_DOWNLOAD_ENSEMBLVEP_SNPEFF": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow cache_download_ensemblvep_snpeff": null, "Leave them out": null}}, "target": "Use nf-core subworkflow cache_download_ensemblvep_snpeff", "target_idx": 2}
{"id": "noul_undeclared_process_file_inputs_18", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Processes in Nextflow DSL2 can directly access files on the host filesystem without declaring them in `input:`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "qc_adapt_pacbio_hifi_0_15", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "For PacBio HiFi circular consensus sequencing (CCS), what is the recommended QC default for FastQC?", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_sortmerna_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Local sequence alignment tool for filtering, mapping and clustering. (tools: SortMeRNA)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hifitrimmer/trim": "Run hifi-trimmer trim to filter and trim adapter-hit regions from PacBio HiFi reads.\nSupports BAM/CRAM/FASTA/F", "mat2json": "converst matlab .mat files into json or csv files.", "sortmerna": "Local sequence alignment tool for filtering, mapping and clustering.", "filtlong": "Filtlong filters long reads based on quality measures or short read data.", "ale": "ALE: assembly likelihood estimator."}}, "target": "sortmerna", "target_idx": 2}
{"id": "local_subworkflow_variantsofint_1_2", "category": "subworkflow_packaging", "state": {"subworkflow": "VARIANTSOFINT", "modules": ["custom/variantsofint"], "description": "Variant filtering and clinical annotation aggregation"}, "question": {"type": "choice", "instructions": "How should this step (custom/variantsofint) be packaged: Variant filtering and clinical annotation aggregation?", "criteria": {"Use nf-core subworkflow variantsofint": null, "Local subworkflow VARIANTSOFINT": null, "Keep the modules in the main workflow": null, "Leave them out": null}}, "target": "Local subworkflow VARIANTSOFINT", "target_idx": 1}
{"id": "pipe_all101_phyloplace_2", "category": "pipeline_routing", "state": "We have raw sequencing data and want to run standard QC, alignment, and quantification for evolution. Best pipeline:", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"pathogensurveillance": "Surveillance of pathogens using population genomics and sequencing [biosurveillance, pathogen-identification]", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline [adna, ancient-dna-analysis, ancientdna]", "nanostring": "An analysis pipeline for Nanostring nCounter expression data. [nanostring, nanostringnorm]", "rangeland": "Pipeline for remotely sensed imagery. The pipeline processes satellite imagery alongside auxiliary data in multiple step", "phyloplace": "nf-core/phyloplace is a bioinformatics best-practice analysis pipeline that performs phylogenetic placement with EPA-NG."}}, "target": "phyloplace", "target_idx": 4}
{"id": "mod_gcta_addgrms_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Combine multiple GRMs listed in an MGRM manifest into a single dense GRM (tools: gcta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gcta_bivariatereml": null, "leviosam2_index": null, "gcta_addgrms": null, "goleft_indexsplit": null, "gcta_fastgwa": null}}, "target": "gcta_addgrms", "target_idx": 2}
{"id": "samplesheet_arch_riboseq_profiling_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/riboseq --input samplesheet.csv (Assay: Ribosome profiling (Ribo-seq) footprint sequencing)", "question": {"type": "choice", "instructions": "Which columns are standard for Ribosome profiling (Ribo-seq) footprint sequencing input samplesheet?", "criteria": {"sample,vcf": null, "sample,bam": null, "sample,fastq_1,strandedness": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,strandedness", "target_idx": 2}
{"id": "field_constraint_bai_2_8", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'bai' (Companion BAM index file) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'bai' validated?", "criteria": {"pattern: ^\\S+\\.crai$": null, "type: boolean": null, "pattern: ^\\S+\\.tbi$": null, "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 3}
{"id": "qc_adapt_illumina_novaseq_0_25", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "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_fasta_gxf_busco_plot_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Runs BUSCO for input assemblies and their annotations in GFF/GFF3/GTF format, and creates summary plots using `busco --plot` (tools: fasta_gxf_busco_plot)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat/convertspgff2tsv": "Converts a GFF/GTF file into a TSV file", "abyss/abysspe": "ABySS is a de novo sequence assembler intended for short paired-end reads and genomes of all sizes.", "gatk4/estimatelibrarycomplexity": "Estimates the numbers of unique molecules in a sequencing library.", "fasta_gxf_busco_plot": "Runs BUSCO for input assemblies and their annotations in GFF/GFF3/GTF format, and creates summary plots using ", "fastk/histex": "A fast K-mer counter for high-fidelity shotgun datasets"}}, "target": "fasta_gxf_busco_plot", "target_idx": 3}
{"id": "pipe_core10_ampliseq_1_described", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? 16S and 18S rRNA amplicon sequencing analysis workflow using DADA2, QIIME2, and taxonomic classification.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. (chip, chip-seq, chromatin-immunoprecipitation, macs2)", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples (amplicon, artic, assembly, covid-19)", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data (classification, illumina", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 (16s, 18s, amplicon-sequencing, edna)", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline (adna, ancient-dna-analysis, ancientdna, genome)", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline (atac-seq, chromatin-accessibiity)", "mag": "Assembly and binning of metagenomes (annotation, assembly, binning, long-read-sequencing)"}}, "target": "ampliseq", "target_idx": 6}
{"id": "mod_echtvar_encode_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Make (encode) a new echtvar file from decomposed vcf (tools: echtvar)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"echtvar_encode": "Make (encode) a new echtvar file from decomposed vcf", "regenie_step2": "Run REGENIE step 2 association testing from precomputed step 1 predictions", "aardvark_compare": "A tool to evaluate variant calling performance by comparing a query VCF against a truth VCF.", "dupradar": "Assessment of duplication rates in RNA-Seq datasets", "bcftools_annotate": "Add or remove annotations."}}, "target": "echtvar_encode", "target_idx": 0}
{"id": "mod_windowmasker_convert_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Masks out highly repetitive DNA sequences with low complexity in a genome (tools: windowmasker)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"windowmasker/convert": "Masks out highly repetitive DNA sequences with low complexity in a genome", "fastqscreen/buildfromindex": "Build fastq screen config file from bowtie index files", "agrvate": "Rapid identification of Staphylococcus aureus agr locus type and agr operon variants", "fasta_index_bismark_bwameth": "Generate index files from reference fasta for bismark and bwameth", "abritamr/run": "A NATA accredited tool for reporting the presence of antimicrobial resistance genes in bacterial genomes"}}, "target": "windowmasker/convert", "target_idx": 0}
{"id": "qc_adapt_pacbio_hifi_1_17", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_hifi_15kb?", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "mod_bwameme_index_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create BWA-MEME index for reference genome (tools: bwameme)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_mergevcfs": "Merges several vcf files", "seqkit_fx2tab": "Convert FASTA/Q to tabular format, and provide various information, like sequence length, GC content/GC skew.", "bowtie_build": "Create bowtie index for reference genome", "bcftools_index": "Index VCF tools", "bwameme_index": "Create BWA-MEME index for reference genome"}}, "target": "bwameme_index", "target_idx": 4}
{"id": "mod_amps_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Post-processing script of the MaltExtract component of the HOPS package (tools: amps)?", "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", "metator_pipeline": "Metagenomic Tridimensional Organisation-based Reassembly - A set of scripts that streamlines the processing an", "malt_build": "MALT, an acronym for MEGAN alignment tool, is a sequence alignment and analysis tool designed for processing h", "ampcombi": "A tool to parse and summarise results from antimicrobial peptides tools and present functional classification.", "amps": "Post-processing script of the MaltExtract component of the HOPS package"}}, "target": "amps", "target_idx": 4}
{"id": "samplesheet_arch_cutandrun_pe_3_1", "category": "samplesheet_schema", "state": {"assay": "CUT&RUN / CUT&TAG chromatin profiling with IgG control", "first_step": "FASTQC", "template": "nf-core/cutandrun"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for CUT&RUN / CUT&TAG chromatin profiling with IgG control with entry step FASTQC.", "criteria": {"sample,fastq_1,fastq_2,target,control": null, "sample,target,control": null, "sample,fastq_1,fastq_2": null, "sample,spikein,fastq": null}}, "target": "sample,fastq_1,fastq_2,target,control", "target_idx": 0}
{"id": "qc_adapt_qc_aggregate_2_47", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample QC aggregation and reporting (multiqc_report).", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "samplesheet_arch_cancer_longitudinal_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/oncoanalyser", "assay_type": "Longitudinal cancer monitoring across multiple timepoints", "data_format": "Serial plasma cfDNA and biopsy FASTQs across treatment intervals"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Longitudinal cancer monitoring across multiple timepoints with entry step FASTQC.", "criteria": {"sample,timepoint,fastq": null, "patient,sample,timepoint,status,fastq_1,fastq_2": null, "patient,sample,bam": null, "sample,fastq_1,fastq_2": null}}, "target": "patient,sample,timepoint,status,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_famsa_align_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Aligns sequences using FAMSA (tools: famsa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"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", "bwa_mem": "Performs fastq alignment to a fasta reference using BWA", "famsa_align": "Aligns sequences using FAMSA", "dia_proteomics_analysis": "Complete DIA-NN proteomics analysis pipeline including in-silico library generation,\npreliminary analysis, emp", "alignoth": "Creating alignment plots from bam files"}}, "target": "famsa_align", "target_idx": 2}
{"id": "resource_atlas_splitmerge_4", "category": "resource_profiling", "state": {"process": "ATLAS_SPLITMERGE", "tool": "atlas/splitmerge", "description": "split single end read groups by length and merge paired end reads"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ATLAS_SPLITMERGE (split single end read groups by length and merge paired end reads) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_high": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_pbmm2_align_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Alignment with PacBio's minimap2 frontend (tools: pbmm2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pbmm2/align": null, "ampcombi2/parsetables": null, "holodeck/simulate": null, "vcontact3/prepareddatabases": null, "ampcombi2/cluster": null}}, "target": "pbmm2/align", "target_idx": 0}
{"id": "mod_telogator2_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Allele-specific telomere length estimation and TVR characterization from long reads (tools: telogator2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"atlas_pmd": null, "atlas_splitmerge": null, "telogator2": null, "shinyngs_app": null, "prokka": null}}, "target": "telogator2", "target_idx": 2}
{"id": "noul_undeclared_process_file_inputs_16", "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_dshbio_filterbed_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filter features in gzipped BED format (tools: dshbio)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_convertbed2gff": "Takes a bed12 file and converts to a GFF3 file", "dshbio_filterbed": "Filter features in gzipped BED format", "cnvpytor_importreaddepth": "command line tool for CNV/CNA analysis. This step imports the read depth data into a root pytor file.", "cadd": "CADD is a tool for scoring the deleteriousness of single nucleotide variants as well as insertion/deletions va", "bedops_convert2bed": "Convert BAM/GFF/GTF/GVF/PSL files to bed"}}, "target": "dshbio_filterbed", "target_idx": 1}
{"id": "mod_deepcell_mesmer_0", "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": {"baysor/run": null, "merquryfk/ploidyplot": null, "deepcell/mesmer": null, "purecn/intervalfile": null, "bftools/showinf": null}}, "target": "deepcell/mesmer", "target_idx": 2}
{"id": "resource_bcftools_norm_3", "category": "resource_profiling", "state": {"process": "BCFTOOLS_NORM", "tool": "bcftools/norm", "description": "Normalize VCF file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_NORM (Normalize VCF file) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 1}
{"id": "resource_bcftools_annotate_3", "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": "qc_adapt_singlecell_multiqc_0_17", "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_methylseq_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/methylseq", "assay": "methylseq pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/methylseq (Methylation (Bisulfite-Sequencing) analysis pipeline using B)?", "criteria": {"ID,Sample,Condition,ReplicateFileName,Fasta": null, "id,path": null, "sample,fastq_1,fastq_2,genome": null, "sample,trait,pascal,twas,additional_sources": null}}, "target": "sample,fastq_1,fastq_2,genome", "target_idx": 2}
{"id": "mod_diamond_deepclust_0", "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": {"custom/clustervisualization": "Generates UMAP and t-SNE visualizations colored by cluster", "custom/clustermetrics": "Computes clustering quality metrics (silhouette, Calinski-Harabasz, Davies-Bouldin) and performs k-sweep analy", "custom/addmostsevereconsequence": "Annotate a VEP annotated VCF with the most severe consequence field", "diamond/deepclust": "Fast graph-based protein sequence clustering using DIAMOND deepclust", "beagle5/beagle": "Beagle v5.5 is a software package for phasing genotypes and for imputing ungenotyped markers."}}, "target": "diamond/deepclust", "target_idx": 3}
{"id": "qc_adapt_pacbio_hifi_0_16", "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": "pipe_all101_metatdenovo_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Assembly and annotation of metatranscriptomic or metagenomic data for prokaryotic, eukaryotic and viruses.. Topics: eukaryotes, metagenomics, metatranscriptomics, prokaryotes, viruses. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"nascent": null, "seqinspector": null, "bacass": null, "sopa": null, "detaxizer": null, "variantbenchmarking": null, "longraredisease": null, "metatdenovo": null, "bactmap": null, "circdna": null}}, "target": "metatdenovo", "target_idx": 7}
{"id": "mod_samtools_addreplacerg_1", "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": {"samtools_addreplacerg": "Adds or replaces read group (RG) tags in BAM/CRAM/SAM files", "cellranger_mkvdjref": "Module to build the VDJ reference needed by the 10x Genomics Cell Ranger tool. Uses the cellranger mkvdjref co", "atlas_splitmerge": "split single end read groups by length and merge paired end reads", "deeptools_plotfingerprint": "plots cumulative reads coverages by BAM file", "abra2": "Assembly Based ReAligner for next-generation sequencing data"}}, "target": "samtools_addreplacerg", "target_idx": 0}
{"id": "local_subworkflow_variantsofint_1_5", "category": "subworkflow_packaging", "state": {"subworkflow": "VARIANTSOFINT", "modules": ["custom/variantsofint"], "description": "Variant filtering and clinical annotation aggregation"}, "question": {"type": "choice", "instructions": "How should this step (custom/variantsofint) be packaged: Variant filtering and clinical annotation aggregation?", "criteria": {"Keep the modules in the main workflow": null, "Leave them out": null, "Local subworkflow VARIANTSOFINT": null, "Use nf-core subworkflow variantsofint": null}}, "target": "Local subworkflow VARIANTSOFINT", "target_idx": 2}
{"id": "samplesheet_arch_viral_amplicon_artic_4_2", "category": "samplesheet_schema", "state": {"assay": "Viral amplicon sequencing with primers", "first_step": "FASTQC"}, "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,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_ciri2_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Circular RNA identification based on multiple seed matching (tools: ciri2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"circexplorer2/parse": "CIRCexplorer2 parses fusion junction files from multiple aligners to prepare them for CIRCexplorer2 annotate.", "gatk4/genotypegvcfs": "Perform joint genotyping on one or more samples pre-called with HaplotypeCaller.", "gecco/run": "GECCO is a fast and scalable method for identifying putative novel Biosynthetic Gene Clusters (BGCs) in genomi", "ganon/buildcustom": "Build ganon database using custom reference sequences.", "ciri2": "Circular RNA identification based on multiple seed matching"}}, "target": "ciri2", "target_idx": 4}
{"id": "samplesheet_arch_faire_seq_chromatin_6_5", "category": "samplesheet_schema", "state": {"assay": "FAIRE-seq / DNAse-seq open chromatin profiling", "first_step": "FASTQC", "inputs": "Formaldehyde-assisted isolation of regulatory elements paired-end FASTQs"}, "question": {"type": "choice", "instructions": "Which columns are standard for FAIRE-seq / DNAse-seq open chromatin profiling input samplesheet?", "criteria": {"sample,bam,bai": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null, "sample,bed": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "schema_std_spatialaxe_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/spatialaxe", "assay": "spatialaxe pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/spatialaxe (A bioinformatics best-practice processing and quality contro)?", "criteria": {"sample,trait,pascal,twas,additional_sources": null, "sample,fastq_1,fastq_2,antibody,control": null, "sample,bundle,image": null, "id,test_vcf,test_regions,caller,subsample": null}}, "target": "sample,bundle,image", "target_idx": 2}
{"id": "samplesheet_arch_scrna_multiome_1_3", "category": "samplesheet_schema", "state": {"assay": "10x Multiome single-cell joint RNA and ATAC chromatin", "first_step": "FASTQC", "inputs": "Paired FASTQs for both GEX and ATAC modalities per nucleus"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for 10x Multiome single-cell joint RNA and ATAC chromatin?", "criteria": {"sample,fastq_1,fastq_2,feature_type": null, "sample,rna_fastq,atac_fastq": null, "sample,matrix": null, "sample,bam": null}}, "target": "sample,fastq_1,fastq_2,feature_type", "target_idx": 0}
{"id": "field_constraint_phenotype_2_11", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'phenotype' (Affection status in clinical trio / family analysis) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'phenotype' validated?", "criteria": {"enum: [normal, tumor]": null, "format: file-path": null, "type: string free-text": null, "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 3}
{"id": "qc_adapt_ont_nanoplot_2_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": "Evaluate the quality control tool choice for: Direct RNA sequencing on Oxford Nanopore PromethION (long_reads_direct_rna).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 1}
{"id": "mod_finaletoolkit_mds_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Comnpute the Motif Diversity Score using normalized Shannon entropy\n(Jiang et al., 2020). (tools: finaletoolkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"agat_spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated", "finaletoolkit_mds": "Comnpute the Motif Diversity Score using normalized Shannon entropy\n(Jiang et al., 2020).", "oarfish_readprojectionmode": "oarfish is a program for quantifying transcript-level expression from long-read sequencing technologies. Splic", "cooler_makebins": "Generate fixed-width genomic bins", "agat_spflagshortintrons": "The script flags the short introns with the attribute <pseudo>. Is is usefull to avoid ERROR when submiting th"}}, "target": "finaletoolkit_mds", "target_idx": 1}
{"id": "resource_agat_convertspgxf2gxf_5", "category": "resource_profiling", "state": {"process": "AGAT_CONVERTSPGXF2GXF", "tool": "agat/convertspgxf2gxf", "description": "Fixes and standardizes GFF/GTF files and outputs a cleaned GFF/GTF file"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_CONVERTSPGXF2GXF (Fixes and standardizes GFF/GTF files and outputs a cleaned GFF/GTF file) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_qc_aggregate_1_44", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Swap for NanoPlot": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_fastq_extract_kraken_krakentools_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extract classified Kraken2 reads by taxonomic id (tools: fastq_extract_kraken_krakentools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"macs2_callpeak": null, "isoseq3_tag": null, "centrifuge_centrifuge": null, "conifer": null, "fastq_extract_kraken_krakentools": null}}, "target": "fastq_extract_kraken_krakentools", "target_idx": 4}
{"id": "qc_adapt_targeted_amplicon_0_39", "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": "qc_adapt_ont_nanoplot_0_20", "category": "qc_read_adaptation", "state": {"assay": "Direct RNA sequencing on Oxford Nanopore PromethION", "tool": "FastQC", "read_type": "long_reads_direct_rna"}, "question": {"type": "choice", "instructions": "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": "qc_adapt_targeted_amplicon_2_19", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Keep FastQC": null, "Swap for NanoPlot": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 0}
{"id": "resource_ampcombi2_cluster_2", "category": "resource_profiling", "state": {"process": "AMPCOMBI2_CLUSTER", "tool": "ampcombi2/cluster", "description": "A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete using MMseqs2 cluster."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMPCOMBI2_CLUSTER (A submodule that clusters the merged AMP hits generated from ampcombi2/parsetabl) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_fgumi_simplex_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calls simplex consensus sequences from reads with the same unique molecular tag.\nThis is a high-performance replacement for fgbio CallMolecularConsensusReads. (tools: fgumi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"hicap": null, "fgbio_callduplexconsensusreads": null, "fgumi_simplex": null, "fgbio_zipperbams": null, "cellranger_mkref": null}}, "target": "fgumi_simplex", "target_idx": 2}
{"id": "noul_channel_filter_operator_21", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.filter { meta, fastq -> meta.single_end }` filters items based on a boolean closure condition.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "qc_adapt_bulk_multiqc_2_47", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "mod_scanpy_pca_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform principal component analysis (PCA) on single-cell RNA-seq data using Scanpy (tools: scanpy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom_clustervisualization": "Generates UMAP and t-SNE visualizations colored by cluster", "picard_bedtointervallist": "Creates an interval list from a bed file and a reference dict", "gatk4_splitncigarreads": "Splits reads that contain Ns in their cigar string", "plink2_pca": "Perform PCA analysis using PLINK", "scanpy_pca": "Perform principal component analysis (PCA) on single-cell RNA-seq data using Scanpy"}}, "target": "scanpy_pca", "target_idx": 4}
{"id": "qc_adapt_targeted_amplicon_2_26", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Swap for NanoPlot": null, "Keep FastQC": null, "Drop FastQC": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "mod_wisecondorx_convert_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Convert and filter aligned reads to .npz (tools: wisecondorx)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"samtools_cramsize": "List CRAM Content-ID and Data-Series sizes", "wisecondorx_convert": "Convert and filter aligned reads to .npz", "atlas_pmd": "Estimate the post-mortem damage patterns of DNA", "abra2": "Assembly Based ReAligner for next-generation sequencing data", "mashmap": "Mashmap is an approximate long read or contig mapper based on Jaccard similarity"}}, "target": "wisecondorx_convert", "target_idx": 1}
{"id": "mod_cnvkit_antitarget_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Derive off-target (“antitarget”) bins from target regions. (tools: cnvkit)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"kmcp/merge": "Merge search results from multiple databases.", "cnvkit/antitarget": "Derive off-target (“antitarget”) bins from target regions.", "cnvkit/reference": "Compile a coverage reference from the given files (normal samples).", "diann": "Generic DIA-NN module for running any DIA-NN operation including in-silico library generation, preliminary ana", "cnvkit/target": "Transform bait intervals into targets more suitable for CNVkit."}}, "target": "cnvkit/antitarget", "target_idx": 1}
{"id": "samplesheet_arch_ont_metagenome_single_7_4", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/mag) for Long-read Oxford Nanopore environmental metagenomic sequencing. Input files: High molecular weight environmental metagenomic long reads per sampling site.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for single-end ONT?", "criteria": {"sample,bam": null, "sample,fasta": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,group": null}}, "target": "sample,fastq_1,group", "target_idx": 3}
{"id": "qc_adapt_singlecell_multiqc_2_24", "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_mdust_0", "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": {"pints/caller": "Main caller script for peak calling", "agat/spmergeannotations": "This script merge different gff annotation files in one. It uses the AGAT parser that takes care of duplicated", "mdust": "mdust from DFCI Gene Indices Software Tools for masking low-complexity DNA sequences", "annotsv/annotsv": "Annotation and Ranking of Structural Variation", "agat/spfilterbyorfsize": "The script reads a gff annotation file, and create two output files, one contains the gene models with ORF pas"}}, "target": "mdust", "target_idx": 2}
{"id": "qc_adapt_singlecell_multiqc_2_29", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample single-cell RNA-seq cohort (summary_reporting).", "criteria": {"Keep MultiQC": null, "Keep FastQC": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "mod_bam_methyldackel_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs methylation quantification based on negative readout of C to T conversion of 3-letter genome alignments using Methyldackel. (tools: bam_methyldackel)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bam_methyldackel": "Performs methylation quantification based on negative readout of C to T conversion of 3-letter genome alignmen", "multiqc": "Aggregate results from bioinformatics analyses across many samples into a single report", "bwameth/index": "Performs indexing of c2t converted reference genome", "bwameth/align": "Performs alignment of BS-Seq reads using bwameth", "admixture": "ADMIXTURE is a program for estimating ancestry in a model-based manner from large autosomal SNP genotype datas"}}, "target": "bam_methyldackel", "target_idx": 0}
{"id": "qc_adapt_ont_ultra_long_1_38", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "How should QC step FastQC be configured given sequencing characteristics: long_reads_20kb_plus?", "criteria": {"Keep FastQC": null, "Drop FastQC": null, "Swap for NanoPlot": null}}, "target": "Swap for NanoPlot", "target_idx": 2}
{"id": "samplesheet_arch_vcf_annotation_pipeline_3_3", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/raredisease", "assay_type": "Downstream functional annotation of pre-called VCF files", "data_format": "BGZF-compressed VCF files with companion Tabix index files"}, "question": {"type": "choice", "instructions": "Define the required samplesheet CSV header schema for Downstream functional annotation of pre-called VCF files with entry step ENSEMBLVEP.", "criteria": {"sample,bed": null, "sample,vcf,tbi": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,vcf,tbi", "target_idx": 1}
{"id": "samplesheet_arch_amplicon_16s_paired_1_4", "category": "samplesheet_schema", "state": {"assay": "16S rRNA / ITS microbiome amplicon profiling", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for 16S rRNA / ITS microbiome amplicon profiling?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fasta": null, "sample,otu_table": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "qc_adapt_pe_illumina_fastqc_0_33", "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": "noul_container_environment_specification_2", "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": "pipe_core10_atacseq_0_bare", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? Chromatin accessibility profiling with hyperactive Tn5 transposase to map genome-wide open chromatin regions and nucleosome positioning.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"ampliseq": null, "eager": null, "sarek": null, "mag": null, "scrnaseq": null, "viralrecon": null, "chipseq": null, "rnaseq": null, "atacseq": null, "taxprofiler": null}}, "target": "atacseq", "target_idx": 8}
{"id": "mod_concoct_cutupfasta_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Cut up fasta file in non-overlapping or overlapping parts of equal length. (tools: concoct)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bedtools/unionbedg": null, "concoct/cutupfasta": null, "dastool/dastool": null, "dastool/fastatocontig2bin": null, "apbs": null}}, "target": "concoct/cutupfasta", "target_idx": 1}
{"id": "mod_geoquery_getgeo_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Retrieves GEO data from the Gene Expression Omnibus (GEO) (tools: geoquery)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rtgtools_rocplot": "Plot ROC curves from vcfeval ROC data files, either to an image, or an interactive GUI. The interactive GUI is", "biscuit_epiread": "Summarizes read-level methylation (and optionally SNV) information from a\nBiscuit BAM file in a standard-compl", "deseq2_differential": "runs a differential expression analysis with DESeq2", "geoquery_getgeo": "Retrieves GEO data from the Gene Expression Omnibus (GEO)", "affy_justrma": "Read CEL files into an ExpressionSet and generate a matrix"}}, "target": "geoquery_getgeo", "target_idx": 3}
{"id": "qc_adapt_qc_aggregate_0_10", "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_propr_propr_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform logratio-based correlation analysis -> get proportionality & basis shrinkage partial correlation coefficients.\nOne can also compute standard correlation coefficients, if required. (tools: propr)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"propr/grea": null, "hisat3n/align": null, "cellranger/mkfastq": null, "propr/propd": null, "propr/propr": null}}, "target": "propr/propr", "target_idx": 4}
{"id": "noul_default_empty_channel_behavior_4", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"In Nextflow DSL2, `Channel.fromPath('data/*.fq')` emits an error if no files match the wildcard pattern by default.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "false", "target_idx": 0}
{"id": "schema_std_ampliseq_1_0", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/ampliseq", "assay": "ampliseq pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/ampliseq (Amplicon sequencing analysis workflow using DADA2 and QIIME2)?", "criteria": {"sample,fastq_1,fastq_2,umi_barcodes": null, "ID,Sample,Condition,ReplicateFileName,Fasta": null, "sample,fastq_1,fastq_2,sampleID,forwardReads": null, "sample,bam,vcf,rna_matrix,hto_matrix": null}}, "target": "sample,fastq_1,fastq_2,sampleID,forwardReads", "target_idx": 2}
{"id": "schema_std_proteinfold_1_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/proteinfold", "assay": "proteinfold pipeline processing", "inputs": "Input files per samplesheet"}, "question": {"type": "choice", "instructions": "What samplesheet columns are expected for Nextflow pipeline nf-core/proteinfold (Protein 3D structure prediction pipeline)?", "criteria": {"sample_id,mapped,index,file_type": null, "sample,bam,pbi,fail,repeat_id": null, "vcf,fasta,genome,site,source": null, "id,fasta,sequence": null}}, "target": "id,fasta,sequence", "target_idx": 3}
{"id": "mod_checkm_lineagewf_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: CheckM provides a set of tools for assessing the quality of genomes recovered from isolates, single cells, or metagenomes. (tools: checkm)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"checkm/lineagewf": "CheckM provides a set of tools for assessing the quality of genomes recovered from isolates, single cells, or ", "panacus/visualize": "Create visualizations from a tsv coverage histogram created with panacus.", "checkm/qa": "CheckM provides a set of tools for assessing the quality of genomes recovered from isolates, single cells, or ", "checkm2/databasedownload": "CheckM2 database download", "purecn/normaldb": "Build a normal database for coverage normalization from all the (GC-normalized) normal coverage files. N.B. as"}}, "target": "checkm/lineagewf", "target_idx": 0}
{"id": "resource_bedtools_bamtobed_5", "category": "resource_profiling", "state": {"process": "BEDTOOLS_BAMTOBED", "tool": "bedtools/bamtobed", "description": "Converts a bam file to a bed12 file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_BAMTOBED (Converts a bam file to a bed12 file.) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "qc_adapt_qc_aggregate_2_39", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample QC aggregation and reporting (multiqc_report).", "criteria": {"Drop MultiQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "mod_amulety_balmpaired_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: A module to create BALM paired embeddings of antibody (BCR) amino acid sequences using amulety. (tools: amulety)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amulety/translate": "A module to translate BCR and TCR nucleotide sequences into amino acid sequences using amulety and igblast.", "amulety/balmpaired": "A module to create BALM paired embeddings of antibody (BCR) amino acid sequences using amulety.", "finaletoolkit/aggbw": "Aggregates a bigWig signal over constant-length intervals\ndefined in a BED file.", "bbmap/bbduk": "Adapter and quality trimming of sequencing reads", "amulety/antiberta2": "A module to create antiberta2 embeddings of antibody (BCR) amino acid sequences using amulety."}}, "target": "amulety/balmpaired", "target_idx": 1}
{"id": "mod_cooler_balance_1", "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": {"ichorcna_createpon": "ichorCNA is an R package for calculating copy number alteration from (low-pass) whole genome sequencing, parti", "cooler_balance": "Run matrix balancing on a cool file", "qualimap_bamqc": "Evaluate alignment data", "cooler_cload": "Create a cooler from genomic pairs and bins", "cooler_digest": "Generate fragment-delimited genomic bins"}}, "target": "cooler_balance", "target_idx": 1}
{"id": "subworkflow_pkg_fastq_sanitise_seqkit_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_SANITISE_SEQKIT", "modules": ["seqkit/sana", "seqkit/pair"], "description": "Filters and reports malformed FASTQ sequences with seqkit/sana,"}, "question": {"type": "choice", "instructions": "How should FASTQ_SANITISE_SEQKIT (seqkit/sana, seqkit/pair) be structured in DSL2?", "criteria": {"Use nf-core subworkflow fastq_sanitise_seqkit": null, "Local subworkflow FASTQ_SANITISE_SEQKIT": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fastq_sanitise_seqkit", "target_idx": 0}
{"id": "mod_checkm2_predict_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: CheckM2 bin quality prediction (tools: checkm2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"star_starsolo": "Create a counts matrix for single-cell data using STARSolo, handling cell barcodes and UMI information.", "repeatmasker_rmouttogff3": "A utility script to assist to convert old RepeatMasker *.out files to version 3 gff files.", "checkm_qa": "CheckM provides a set of tools for assessing the quality of genomes recovered from isolates, single cells, or ", "checkm2_predict": "CheckM2 bin quality prediction", "checkv_endtoend": "Assess the quality of metagenome-assembled viral genomes."}}, "target": "checkm2_predict", "target_idx": 3}
{"id": "qc_adapt_pe_illumina_fastqc_2_46", "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_subread_featurecounts_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Count reads that map to genomic features (tools: featurecounts)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"subread_featurecounts": "Count reads that map to genomic features", "dshbio_splitgff3": "Split features in gzipped GFF3 format", "samtools_idxstats": "Reports alignment summary statistics for a BAM/CRAM/SAM file", "kaiju_kaiju": "Taxonomic classification of metagenomic sequence data using a protein reference database", "custom_rsemmergecounts": "Merge per-sample RSEM results into wide and long format TSV matrices"}}, "target": "subread_featurecounts", "target_idx": 0}
{"id": "resource_amplify_predict_3", "category": "resource_profiling", "state": {"process": "AMPLIFY_PREDICT", "tool": "amplify/predict", "description": "AMPlify is an attentive deep learning model for antimicrobial peptide prediction."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMPLIFY_PREDICT (AMPlify is an attentive deep learning model for antimicrobial peptide prediction) in conf/base.config?", "criteria": {"process_high": null, "process_long": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_custom_tabulartogseachip_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Make a GSEA class file (.chip) from tabular inputs (tools: custom)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gsea/gsea": "run the Broad Gene Set Enrichment tool in GSEA mode", "custom/tabulartogseachip": "Make a GSEA class file (.chip) from tabular inputs", "bamtofastq10x": "Tool for converting 10x BAMs produced by Cell Ranger, Space Ranger, Cell Ranger ATAC, Cell Ranger DNA, and Lon", "octopusv/plotcircos": "Draw a genome-wide structural variant Circos plot from an OctopuSV SVCF file.", "somalier/ancestry": "Somalier can extract informative sites, evaluate relatedness, and perform quality-control on BAM/CRAM/BCF/VCF/"}}, "target": "custom/tabulartogseachip", "target_idx": 1}
{"id": "mod_gcta_bivariateremlldms_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Run bivariate REML-LDMS analysis with an MGRM manifest (tools: gcta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gcta/grmcutoff": "Apply a genetic relationship cutoff to a dense GRM using `gcta --grm-cutoff`", "gcta/fastgwa": "Run GCTA fastGWA mixed linear model association analysis with PLINK genotype inputs", "bioformats2raw": "Java application to convert image file formats, including .mrxs, to an intermediate Zarr structure compatible ", "bam_impute_stitch": "Subworkflow to impute BAM files using STITCH software.\nVariants location to impute are obtain through the lege", "gcta/bivariateremlldms": "Run bivariate REML-LDMS analysis with an MGRM manifest"}}, "target": "gcta/bivariateremlldms", "target_idx": 4}
{"id": "mod_links_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: LINKS is a genomics application for scaffolding genome assemblies with long reads,\nsuch as those produced by Oxford Nanopore Technologies Ltd.\nIt can be used to scaffold high-quality draft genome assemblies with any long sequences\n(eg. ONT reads, PacBio reads, other draft genomes, etc).\nIt is also used to scaffold contig pairs linked by ARCS/ARKS.\nThis module is for LINKS >=2.0.0 and does not support MPET input. (tools: links)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bbmap_index": "Creates an index from a fasta file, ready to be used by bbmap.sh in mapping mode.", "svtk_rdtest2vcf": "Convert an RdTest-formatted bed to the standard VCF format.", "quast": "Quality Assessment Tool for Genome Assemblies", "vclust_align": "The align command performs pairwise sequence alignments of viral genomes and provides similarity measures like", "links": "LINKS is a genomics application for scaffolding genome assemblies with long reads,\nsuch as those produced by O"}}, "target": "links", "target_idx": 4}
{"id": "pipe_all101_slamseq_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: SLAMSeq processing and analysis pipeline. Topics: differential-expression, quantseq, slamseq, transcriptomics. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"molkart": null, "fastqrepair": null, "circdna": null, "pangenome": null, "proteinannotator": null, "slamseq": null, "eager": null, "rnaseq": null}}, "target": "slamseq", "target_idx": 5}
{"id": "noul_channel_mix_operator_10", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.mix()` combines two or more channels of identical emission structure into a single unified stream.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_ribocode_metaplots_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Set up RiboCode ORF calling with metaplots (tools: ribocode)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ribocode/gtfupdate": null, "seqkit/translate": null, "cnvkit/batch": null, "ribocode/ribocode": null, "ribocode/metaplots": null}}, "target": "ribocode/metaplots", "target_idx": 4}
{"id": "samplesheet_arch_ancient_dna_eager_6_0", "category": "samplesheet_schema", "state": {"technology": "Ancient DNA", "workflow_entry": "FASTQC", "library_inputs": "Ancient degraded DNA FASTQs with library preparation chemistry and uracil-DNA-glycosylase status"}, "question": {"type": "choice", "instructions": "Which columns are standard for Ancient DNA (aDNA) sequencing with UDG treatment and damage assessment input samplesheet?", "criteria": {"sample,fastq_1,fastq_2": null, "patient,sample,status,fastq_1,fastq_2": null, "sample,library_id,fastq_1,fastq_2": null, "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2": null}}, "target": "sample,library_id,lane,colour_chemistry,seq_type,paired_end,udg,strandedness,fastq_1,fastq_2", "target_idx": 3}
{"id": "mod_mirdeep2_mirdeep2_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: miRDeep2 is a tool for identifying known and novel miRNAs in deep sequencing data by analyzing sequenced RNAs. It integrates the mapping of sequencing reads to the genome and predicts miRNA precursors and mature miRNAs. (tools: mirdeep2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"knotannotsv": "Simple tool to create a customizable html file (to be displayed on a web browser) from an AnnotSV output", "gem2_gemmappability": "Define the mappability of a reference", "mirdeep2_mirdeep2": "miRDeep2 is a tool for identifying known and novel miRNAs in deep sequencing data by analyzing sequenced RNAs.", "mirdeep2_mapper": "miRDeep2 Mapper is a tool that prepares deep sequencing reads for downstream miRNA detection by collapsing rea", "fastq_find_mirna_mirdeep2": "This subworkflow identifies miRNAs from FASTQ files using miRDeep2. The workflow converts FASTQ to FASTA, proc"}}, "target": "mirdeep2_mirdeep2", "target_idx": 2}
{"id": "mod_unicycler_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Assembles bacterial genomes (tools: unicycler)?", "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", "hhsuite/reformat": "Reformat a Multiple Sequence Alignment (MSA) file", "plastid/makewiggle": "Create wiggle or bedGraph files from alignment files after applying a read mapping rule (e.g. to map ribosome-", "abyss/abysspe": "ABySS is a de novo sequence assembler intended for short paired-end reads and genomes of all sizes.", "unicycler": "Assembles bacterial genomes"}}, "target": "unicycler", "target_idx": 4}
{"id": "mod_fgumi_merge_0", "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", "bcftools/merge": "Merge VCF files", "atlas/splitmerge": "split single end read groups by length and merge paired end reads", "mobsuite/recon": "A tool to reconstruct plasmids in bacterial assemblies", "quantify_pseudo_alignment": "Perform quantification with Salmon or Kallisto to produce count tables and SummarizedExperiment objects"}}, "target": "fgumi/merge", "target_idx": 0}
{"id": "samplesheet_arch_bacterial_hybrid_assembly_2_5", "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?", "criteria": {"sample,fastq_1": null, "sample,fastq_1,fastq_2,long_fastq": null, "sample,bam": null, "sample,fasta": null}}, "target": "sample,fastq_1,fastq_2,long_fastq", "target_idx": 1}
{"id": "noul_publishdir_directive_usage_23", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Process outputs can be conditionally saved to disk using the `publishDir` directive with `mode: 'copy'` or `mode: 'symlink'`.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_ont_metagenome_single_7_5", "category": "samplesheet_schema", "state": "nextflow run nf-core/mag --input samplesheet.csv (Assay: Long-read Oxford Nanopore environmental metagenomic sequencing)", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for single-end ONT?", "criteria": {"sample,fasta": null, "sample,fastq_1,fastq_2,group": null, "sample,fastq_1,group": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,group", "target_idx": 2}
{"id": "resource_anarcii_0", "category": "resource_profiling", "state": {"process": "ANARCII", "tool": "anarcii", "description": "A language model for antigen receptor numbering"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANARCII (A language model for antigen receptor numbering) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_low": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_gatk4_splitncigarreads_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Splits reads that contain Ns in their cigar string (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4/applybqsr": null, "gvcftools/extractvariants": null, "gatk4/annotateintervals": null, "clustalo/align": null, "gatk4/splitncigarreads": null}}, "target": "gatk4/splitncigarreads", "target_idx": 4}
{"id": "qc_adapt_illumina_novaseq_2_49", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "qc_adapt_ont_ultra_long_0_23", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "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": "field_constraint_expected_cells_2_0", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'expected_cells' (Expected cell count in single-cell droplet pipelines) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'expected_cells' validated?", "criteria": {"format: file-path": null, "enum: [auto, single, paired]": null, "type: integer, minimum: 100, maximum: 50000": null, "pattern: ^\\S+\\.csv$": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 2}
{"id": "field_constraint_phenotype_0_9", "category": "samplesheet_schema", "state": {"field_name": "phenotype", "datatype": "pedigree_phenotype_enum", "description": "Affection status in clinical trio / family analysis"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'phenotype'?", "criteria": {"type: string free-text": null, "format: file-path": null, "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null, "enum: [normal, tumor]": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 2}
{"id": "mod_plink_epistasis_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Epistasis in PLINK, analyzing how the effects of one gene depend on the presence of others. (tools: plink)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"svtk/rdtest2vcf": null, "lsa/cosine": null, "plink/epistasis": null, "plink/fastepistasis": null, "freyja/boot": null}}, "target": "plink/epistasis", "target_idx": 2}
{"id": "mod_fibertoolsrs_addnucleosomes_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Add nucleosomes positions and MSP position to ONT BAM files (tools: fibertoolsrs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bismark_genomepreparation": null, "custom_geneticmapconvert": null, "bismark_deduplicate": null, "fibertoolsrs_addnucleosomes": null, "kraken2_buildstandard": null}}, "target": "fibertoolsrs_addnucleosomes", "target_idx": 3}
{"id": "resource_bcftools_pluginsetgt_4", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINSETGT", "tool": "bcftools/pluginsetgt", "description": "Sets genotypes according to the specified criteria and filtering expressions. For example, missing genotypes can be set to ref, but much more than that."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINSETGT (Sets genotypes according to the specified criteria and filtering expressions. Fo) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_medium": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_anota2seq_anota2seqrun_2", "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_high": null, "process_low": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "mod_hpsuissero_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Serotype prediction of Haemophilus parasuis assemblies (tools: hpsuissero)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"untarfiles": "Extract files.", "amrfinderplus_update": "Identify antimicrobial resistance in gene or protein sequences", "amrfinderplus_run": "Identify antimicrobial resistance in gene or protein sequences", "scanpy_hashsolo": "Probabilistic demultiplexing of cell hashing data", "hpsuissero": "Serotype prediction of Haemophilus parasuis assemblies"}}, "target": "hpsuissero", "target_idx": 4}
{"id": "resource_bamtools_stats_1", "category": "resource_profiling", "state": {"process": "BAMTOOLS_STATS", "tool": "bamtools/stats", "description": "BamTools provides both a programmer's API and an end-user's toolkit for handling BAM files."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMTOOLS_STATS (BamTools provides both a programmer's API and an end-user's toolkit for handling) in conf/base.config?", "criteria": {"process_single": null, "process_long": null, "process_medium": null, "process_high": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_nanofilt_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Filtering and trimming of Oxford Nanopore Sequencing data (tools: nanofilt)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"pridepy_downloadfile": "Download a single file from the PRIDE Archive by name using pridepy.", "trgt_merge": "Merge TRGT VCFs from multiple samples", "dragonflye": "Assemble bacterial isolate genomes from Nanopore reads", "emu_abundance": "A taxonomic profiler for metagenomic 16S data optimized for error prone long reads.", "nanofilt": "Filtering and trimming of Oxford Nanopore Sequencing data"}}, "target": "nanofilt", "target_idx": 4}
{"id": "mod_mcstaging_phenoimager2mc_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Staging module for MCMICRO transforming PhenoImager .tif files into stacked and normalized ome-tif files per cycle, compatible as ASHLAR input. (tools: mcstaging)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mcstaging/phenoimager2mc": "Staging module for MCMICRO transforming PhenoImager .tif files into stacked and normalized ome-tif files per c", "porechop/porechop": "Adapter removal and demultiplexing of Oxford Nanopore reads", "deepcell/mesmer": "Deepcell/mesmer segmentation for whole-cell", "basicpy": "BaSiCPy is a python package for background and shading correction of optical microscopy images. It is develope", "macs3/callpeak": "Peak calling of enriched genomic regions of ChIP-seq and ATAC-seq experiments"}}, "target": "mcstaging/phenoimager2mc", "target_idx": 0}
{"id": "mod_samtools_mpileup_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate text pileup output for one or multiple BAM files. Each input file produces a separate group of pileup columns in the output. (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"abra2": "Assembly Based ReAligner for next-generation sequencing data", "samtools_mpileup": "Generate text pileup output for one or multiple BAM files. Each input file produces a separate group of pileup", "crabs_insilicopcr": "CRABS extracts the amplicon region of the primer set by conducting an in silico PCR.", "fgumi_duplex": "Calls duplex consensus sequences from reads generated from the same double-stranded\nsource molecule. This is a", "ascat": "copy number profiles of tumour cells."}}, "target": "samtools_mpileup", "target_idx": 1}
{"id": "mod_gappa_examineassign_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: assigns taxonomy to query sequences in phylogenetic placement output (tools: gappa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"epang_place": "phylogenetic placement of query sequences in a reference tree", "cmaple": "Efficient phylogenetic tree reconstruction for sequences using the CMAPLE algorithm", "rseqc_junctionsaturation": "compare detected splice junctions to reference gene model", "gappa_examineassign": "assigns taxonomy to query sequences in phylogenetic placement output", "blobtk_snail": "Creates blobtk snail plots."}}, "target": "gappa_examineassign", "target_idx": 3}
{"id": "pipe_all101_pacvar_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for alignment analysis? Specific context: Longread PacBio sequencing processing for WGS and PureTarget. Topics: alignment, long-read, pacbio, puretarget, variant-calling, wgs. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 [16s, 18s, amplicon-sequencing]", "genomeassembler": "Assembly and scaffolding of haploid / unphased genomes from long ONT or PacBio HiFi reads [genome-assembly]", "metaboigniter": "Pre-processing of mass spectrometry-based metabolomics data with quantification and identification based on MS1 and MS2 ", "dualrnaseq": "Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous", "pacvar": "Longread PacBio sequencing processing for WGS and PureTarget [alignment, long-read, pacbio]"}}, "target": "pacvar", "target_idx": 4}
{"id": "mod_bwamem2_mem_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs fastq alignment to a fasta reference using BWA (tools: bwamem2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vcftools": "A set of tools written in Perl and C++ for working with VCF files", "scanpy/pca": "Perform principal component analysis (PCA) on single-cell RNA-seq data using Scanpy", "bwa/mem": "Performs fastq alignment to a fasta reference using BWA", "sentieon/bwamem": "Performs fastq alignment to a fasta reference using Sentieon's BWA MEM", "bwamem2/mem": "Performs fastq alignment to a fasta reference using BWA"}}, "target": "bwamem2/mem", "target_idx": 4}
{"id": "mod_bbmap_align_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Align short or PacBio reads to a reference genome using BBMap (tools: bbmap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ampcombi2_cluster": "A submodule that clusters the merged AMP hits generated from ampcombi2/parsetables and ampcombi2/complete usin", "rtn_tni": "Uses the RTN R package for transcriptional regulatory network inference (TNI).", "ampcombi2_complete": "A submodule that merges all output summary tables from ampcombi/parsetables in one summary file.", "bbmap_align": "Align short or PacBio reads to a reference genome using BBMap", "vcf2zarr_convert": "Convert VCF data to the VCF Zarr specification reliably, in parallel or distributed over a cluster"}}, "target": "bbmap_align", "target_idx": 3}
{"id": "subworkflow_pkg_bam_dedup_stats_samtools_umitools_0", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_DEDUP_STATS_SAMTOOLS_UMITOOLS", "modules": ["umitools/dedup", "samtools/index", "samtools/view", "samtools/stats", "samtools/idxstats", "samtools/flagstat", "bam_stats_samtools"], "description": "UMI-tools dedup, index BAM file and run samtools stats, flagstat and idxstats"}, "question": {"type": "choice", "instructions": "How should BAM_DEDUP_STATS_SAMTOOLS_UMITOOLS (umitools/dedup, samtools/index, samtools/view, samtools/stats, samtools/idxstats, samtools/flagstat, bam_stats_samtools) be structured in DSL2?", "criteria": {"Keep the modules in the main workflow": null, "Local subworkflow BAM_DEDUP_STATS_SAMTOOLS_UMITOOLS": null, "Leave them out": null, "Use nf-core subworkflow bam_dedup_stats_samtools_umitools": null}}, "target": "Use nf-core subworkflow bam_dedup_stats_samtools_umitools", "target_idx": 3}
{"id": "field_constraint_expected_cells_1_6", "category": "samplesheet_schema", "state": {"column": "expected_cells", "purpose": "Expected cell count in single-cell droplet pipelines"}, "question": {"type": "choice", "instructions": "Determine the schema validation rule for field 'expected_cells' (Expected cell count in single-cell droplet pipelines).", "criteria": {"enum: [auto, single, paired]": null, "type: integer, minimum: 100, maximum: 50000": null, "format: file-path": null, "pattern: ^\\S+\\.csv$": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 1}
{"id": "resource_autocycler_compress_1", "category": "resource_profiling", "state": {"process": "AUTOCYCLER_COMPRESS", "tool": "autocycler/compress", "description": "Package candidate assemblies for clustering by Autocycler."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AUTOCYCLER_COMPRESS (Package candidate assemblies for clustering by Autocycler.) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_long": null, "process_low": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_bbmap_clumpify_1", "category": "resource_profiling", "state": {"process": "BBMAP_CLUMPIFY", "tool": "bbmap/clumpify", "description": "Create 30% Smaller, Faster Gzipped Fastq Files. And remove duplicates"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BBMAP_CLUMPIFY (Create 30% Smaller, Faster Gzipped Fastq Files. And remove duplicates) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "mod_kaiju_mkfmi_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Make Kaiju FMI-index file from a protein FASTA file (tools: kaiju)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rpbp/estimatemetagenebayesfactors": null, "conifer": null, "centrifuge/kreport": null, "savana/classify": null, "kaiju/mkfmi": null}}, "target": "kaiju/mkfmi", "target_idx": 4}
{"id": "resource_ampcombi2_complete_3", "category": "resource_profiling", "state": {"process": "AMPCOMBI2_COMPLETE", "tool": "ampcombi2/complete", "description": "A submodule that merges all output summary tables from ampcombi/parsetables in one summary file."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AMPCOMBI2_COMPLETE (A submodule that merges all output summary tables from ampcombi/parsetables in o) in conf/base.config?", "criteria": {"process_long": null, "process_low": null, "process_single": null, "process_medium": null}}, "target": "process_single", "target_idx": 2}
{"id": "qc_adapt_pacbio_hifi_2_16", "category": "qc_read_adaptation", "state": {"assay": "PacBio HiFi circular consensus sequencing (CCS)", "tool": "FastQC", "read_type": "long_reads_hifi_15kb"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: PacBio HiFi circular consensus sequencing (CCS) (long_reads_hifi_15kb).", "criteria": {"Swap for NanoPlot": null, "Drop FastQC": null, "Keep FastQC": null}}, "target": "Swap for NanoPlot", "target_idx": 0}
{"id": "mod_pureclip_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: PureCLIP is a tool to detect protein-RNA interaction footprints from single-nucleotide CLIP-seq data, such as iCLIP and eCLIP. (tools: pureclip)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"icountmini_metagene": "Plot a metagene of cross-link events/sites around various transcriptomic landmarks.", "pureclip": "PureCLIP is a tool to detect protein-RNA interaction footprints from single-nucleotide CLIP-seq data, such as ", "mmseqs_contig_taxonomy": "Assign taxonomy to contigs using the MMseqs2 workflow.", "clippy": "Runs the Clippy CLIP peak caller", "metaspace_converter": "Export METASPACE datasets to AnnData and SpatialData objects"}}, "target": "pureclip", "target_idx": 1}
{"id": "mod_epic2_epic2_0", "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": {"epic2/epic2": "Domain calling of broad enriched genomic regions of ChIP-seq, Cut&Run or Cut&Tag", "biscuit/align": "Aligns single- or paired-end reads from bisulfite-converted libraries to a reference genome using Biscuit.", "rclone/checksum": "Check files in a destination path against a checksum SUM file", "ashlar": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration", "amps": "Post-processing script of the MaltExtract component of the HOPS package"}}, "target": "epic2/epic2", "target_idx": 0}
{"id": "mod_vcontact3_prepareddatabases_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Prepare and format databases for vCONTACT3 viral taxonomic analysis (tools: vcontact3)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"vcontact3/prepareddatabases": "Prepare and format databases for vCONTACT3 viral taxonomic analysis", "gatk4/haplotypecaller": "Call germline SNPs and indels via local re-assembly of haplotypes", "cobrameta": "A tool to raise the quality of viral genomes assembled from short-read metagenomes via resolving and joining o", "checkv/downloaddatabase": "Construct the database necessary for checkv's quality assessment", "picard/collectrnaseqmetrics": "Collect metrics from a RNAseq BAM file"}}, "target": "vcontact3/prepareddatabases", "target_idx": 0}
{"id": "mod_last_mafswap_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Reorder alignments in a MAF file (tools: last)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"last_postmask": "Post-alignment masking", "last_mafswap": "Reorder alignments in a MAF file", "last_mafconvert": "Converts MAF alignments in another format.", "bam2fastx_bam2fastq": "Conversion of PacBio BAM files into gzipped fastq files, including splitting of barcoded data", "hhsuite_reformat": "Reformat a Multiple Sequence Alignment (MSA) file"}}, "target": "last_mafswap", "target_idx": 1}
{"id": "mod_metabat2_metabat2_0", "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": null, "metabat2/metabat2": null, "mmseqs/search": null, "picard/meanqualitybycycle": null, "bedtools/sort": null}}, "target": "metabat2/metabat2", "target_idx": 1}
{"id": "mod_gatk4_variantstotable_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extract fields from a VCF file to a tab-delimited table (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"idemux": "Demultiplex paired-end FASTQ files from QuantSeq-Pool", "kallistobustools/ref": "index creation for kb count quantification of single-cell data.", "gatk4/variantstotable": "Extract fields from a VCF file to a tab-delimited table", "bamcmp": "Bamcmp (Bam Compare) is a tool for assigning reads between a primary genome and a contamination genome. For in", "arcane/filter": "Filter GTF annotations and genome sequence for alignment-free single-cell RNA-seq quantification with Arcane"}}, "target": "gatk4/variantstotable", "target_idx": 2}
{"id": "samplesheet_arch_singlecell_parse_splitseq_0_1", "category": "samplesheet_schema", "state": {"assay": "Parse Biosciences Split-seq combinatorial barcoding", "first_step": "FASTQC", "inputs": "Combinatorial split-pool barcoded FASTQs with subpool annotations"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Parse Biosciences Split-seq combinatorial barcoding?", "criteria": {"sample,fastq_1": null, "sample,subpool,fastq_1,fastq_2": null, "sample,bam": null, "sample,well,plate": null}}, "target": "sample,subpool,fastq_1,fastq_2", "target_idx": 1}
{"id": "mod_foldseek_createdb_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Create a database from protein structures (tools: foldseek)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bcftools_csq": "bcftools Haplotype-aware consequence caller", "seqfu_stats": "Statistics for FASTA or FASTQ files", "tailfindr": "Estimating poly(A)-tail lengths from basecalled fast5 files produced by Nanopore sequencing of RNA and DNA", "cdhit_cdhit": "Cluster protein sequences using sequence similarity", "foldseek_createdb": "Create a database from protein structures"}}, "target": "foldseek_createdb", "target_idx": 4}
{"id": "resource_bwa_mem_4", "category": "resource_profiling", "state": {"process": "BWA_MEM", "tool": "bwa/mem", "description": "Performs fastq alignment to a fasta reference using BWA"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWA_MEM (Performs fastq alignment to a fasta reference using BWA) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_high": null, "process_medium": null}}, "target": "process_high", "target_idx": 2}
{"id": "subworkflow_pkg_bam_markduplicates_samtools_3", "category": "subworkflow_packaging", "state": {"subworkflow": "BAM_MARKDUPLICATES_SAMTOOLS", "modules": ["samtools/collate", "samtools/fixmate", "samtools/sort", "samtools/markdup"], "description": "Samtools markduplicate SAM/BAM/CRAM file"}, "question": {"type": "choice", "instructions": "How should BAM_MARKDUPLICATES_SAMTOOLS (samtools/collate, samtools/fixmate, samtools/sort, samtools/markdup) be structured in DSL2?", "criteria": {"Leave them out": null, "Use nf-core subworkflow bam_markduplicates_samtools": null, "Local subworkflow BAM_MARKDUPLICATES_SAMTOOLS": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow bam_markduplicates_samtools", "target_idx": 1}
{"id": "mod_custom_getchromsizes_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generates a FASTA file of chromosome sizes and a fasta index file (tools: samtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bbmap_index": null, "amrfinderplus_run": null, "custom_getchromsizes": null, "abritamr_run": null, "drep_compare": null}}, "target": "custom_getchromsizes", "target_idx": 2}
{"id": "mod_tar_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Compress directories into tarballs with various compression options (tools: tar)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"dshbio_splitbed": "Split features in gzipped BED format", "autocycler_compress": "Package candidate assemblies for clustering by Autocycler.", "foldcomp_compress": "Efficient compression tool for protein structures", "hostile_fetch": "Downloads required reference genomes for Hostile", "tar": "Compress directories into tarballs with various compression options"}}, "target": "tar", "target_idx": 4}
{"id": "subworkflow_pkg_fasta_build_add_kraken2_2", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_BUILD_ADD_KRAKEN2", "modules": ["kraken2/add", "kraken2/build"], "description": "KRAKEN2 build custom database subworkflow"}, "question": {"type": "choice", "instructions": "How should FASTA_BUILD_ADD_KRAKEN2 (kraken2/add, kraken2/build) be structured in DSL2?", "criteria": {"Leave them out": null, "Local subworkflow FASTA_BUILD_ADD_KRAKEN2": null, "Use nf-core subworkflow fasta_build_add_kraken2": null, "Keep the modules in the main workflow": null}}, "target": "Use nf-core subworkflow fasta_build_add_kraken2", "target_idx": 2}
{"id": "resource_bcftools_pluginscatter_4", "category": "resource_profiling", "state": {"process": "BCFTOOLS_PLUGINSCATTER", "tool": "bcftools/pluginscatter", "description": "Split VCF by chunks or regions, creating multiple VCFs."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BCFTOOLS_PLUGINSCATTER (Split VCF by chunks or regions, creating multiple VCFs.) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_single": null, "process_long": null}}, "target": "process_single", "target_idx": 2}
{"id": "pipe_core10_viralrecon_2_bare", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? Viral metagenomics, reference-guided assembly, and mutation calling for amplicon and metagenomic libraries.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"taxprofiler": null, "scrnaseq": null, "chipseq": null, "eager": null, "sarek": null, "ampliseq": null, "viralrecon": null, "mag": null, "atacseq": null, "rnaseq": null}}, "target": "viralrecon", "target_idx": 6}
{"id": "mod_seqtk_seq_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Common transformation operations on FASTA or FASTQ files. (tools: seqtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"varlociraptor/filterfdr": "Filter Varlociraptor variant calls using FDR control.", "graphtyper/vcfconcatenate": "Tools for population-scale genotyping using pangenome graphs.", "agat/spkeeplongestisoform": "Filters GFF records to keep only the longest isoform per gene", "seqtk/seq": "Common transformation operations on FASTA or FASTQ files.", "biscuit/bsconv": "Summarize and/or filter reads based on bisulfite conversion rate"}}, "target": "seqtk/seq", "target_idx": 3}
{"id": "local_subworkflow_positionsofint_1_3", "category": "subworkflow_packaging", "state": {"subworkflow": "POSITIONSOFINT", "modules": ["custom/positionsofint"], "description": "Position of interest depth extraction"}, "question": {"type": "choice", "instructions": "How should this step (custom/positionsofint) be packaged: Position of interest depth extraction?", "criteria": {"Leave them out": null, "Use nf-core subworkflow positionsofint": null, "Local subworkflow POSITIONSOFINT": null, "Keep the modules in the main workflow": null}}, "target": "Local subworkflow POSITIONSOFINT", "target_idx": 2}
{"id": "mod_mmseqs_createindex_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Creates sequence index for mmseqs database (tools: mmseqs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"freyja/demix": "specify the relative abundance of each known haplotype", "mmseqs/easycluster": "Cluster sequences using MMSeqs2 easy cluster.", "pychopper": "Identify, orient and trim nanopore cDNA reads", "mmseqs/createtsv": "Create a tsv file from a query and a target database as well as the result database", "mmseqs/createindex": "Creates sequence index for mmseqs database"}}, "target": "mmseqs/createindex", "target_idx": 4}
{"id": "field_constraint_expected_cells_3_3", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "expected_cells", "validation_type": "numeric_integer"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'expected_cells'.", "criteria": {"format: file-path": null, "enum: [auto, single, paired]": null, "type: integer, minimum: 100, maximum: 50000": null, "pattern: ^\\S+\\.csv$": null}}, "target": "type: integer, minimum: 100, maximum: 50000", "target_idx": 2}
{"id": "resource_bowtie2_build_3", "category": "resource_profiling", "state": {"process": "BOWTIE2_BUILD", "tool": "bowtie2/build", "description": "Builds bowtie index for reference genome"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BOWTIE2_BUILD (Builds bowtie index for reference genome) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_trimal_1", "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": {"hmmer_hmmalign": "hmmalign from the HMMER suite aligns a number of sequences to an HMM profile", "trimal": "trimAl is a tool for the automated removal of spurious sequences or poorly aligned regions from a multiple seq", "busco_phylogenomics": "Construct species phylogenies using BUSCO proteins", "samtools_fastq": "Converts a SAM/BAM/CRAM file to FASTQ", "ashlar": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration"}}, "target": "trimal", "target_idx": 1}
{"id": "mod_antismash_antismashlite_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: antiSMASH allows the rapid genome-wide identification, annotation\nand analysis of secondary metabolite biosynthesis gene clusters. (tools: antismashlite)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"deepbgc/pipeline": null, "hificnv": null, "holodeck/methylate": null, "antismash/antismashlite": null, "antismash/antismashlitedownloaddatabases": null}}, "target": "antismash/antismashlite", "target_idx": 3}
{"id": "samplesheet_arch_viral_amplicon_artic_5_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": "In Nextflow pipeline nf-core/viralrecon, determine the input samplesheet column structure for: Viral amplicon sequencing with primers.", "criteria": {"sample,fasta": null, "sample,fastq_1,fastq_2": null, "sample,bam": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "qc_adapt_singlecell_multiqc_0_33", "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": "noul_channel_mix_operator_24", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.mix()` combines two or more channels of identical emission structure into a single unified stream.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "intent_prepare_data_21", "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, "ask_question": null, "build_pipeline": null, "debug_error": null}}, "target": "prepare_data", "target_idx": 0}
{"id": "samplesheet_arch_epigenomics_hic_0_0", "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 for: Hi-C chromosome conformation capture mapping?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,matrix,contacts": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 3}
{"id": "pipe_core10_atacseq_1_described", "category": "pipeline_routing", "state": "Which released nf-core pipeline is specifically built for this assay? Assay for Transposase-Accessible Chromatin to quantify differential accessibility between drug-treated and untreated lymphocytes.", "question": {"type": "choice", "instructions": "Select the released nf-core pipeline designed for this assay.", "criteria": {"chipseq": "ChIP-seq peak-calling, QC and differential analysis pipeline. (chip, chip-seq, chromatin-immunoprecipitation, macs2)", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline (adna, ancient-dna-analysis, ancientdna, genome)", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "mag": "Assembly and binning of metagenomes (annotation, assembly, binning, long-read-sequencing)", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data (classification, illumina", "scrnaseq": "Single-cell RNA-Seq pipeline for barcode-based protocols such as 10x, DropSeq or SmartSeq, offering a variety of aligner", "atacseq": "ATAC-seq peak-calling and QC analysis pipeline (atac-seq, chromatin-accessibiity)", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 (16s, 18s, amplicon-sequencing, edna)", "viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples (amplicon, artic, assembly, covid-19)"}}, "target": "atacseq", "target_idx": 7}
{"id": "mod_dastool_scaffolds2bin_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Helper script to convert a set of bins in fasta format to tabular scaffolds2bin format (tools: dastool)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amps": null, "dastool_scaffolds2bin": null, "merquryfk_hapmaker": null, "concoct_concoct": null, "clame": null}}, "target": "dastool_scaffolds2bin", "target_idx": 1}
{"id": "subworkflow_pkg_fasta_gtf_bam_rpbp_1", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTA_GTF_BAM_RPBP", "modules": ["rpbp/preparegenome", "rpbp/extractmetageneprofiles", "rpbp/estimatemetagenebayesfactors", "rpbp/selectperiodicoffsets", "rpbp/getperiodiclengthsoffsets", "rpbp/extractorfprofiles", "rpbp/estimateorfbayesfactors", "rpbp/selectfinalpredictionset"], "description": "End-to-end translated-ORF discovery from ribosome profiling (Ribo-seq) data"}, "question": {"type": "choice", "instructions": "How should FASTA_GTF_BAM_RPBP (rpbp/preparegenome, rpbp/extractmetageneprofiles, rpbp/estimatemetagenebayesfactors, rpbp/selectperiodicoffsets, rpbp/getperiodiclengthsoffsets, rpbp/extractorfprofiles, rpbp/estimateorfbayesfactors, rpbp/selectfinalpredictionset) be structured in DSL2?", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Local subworkflow FASTA_GTF_BAM_RPBP": null, "Use nf-core subworkflow fasta_gtf_bam_rpbp": null}}, "target": "Use nf-core subworkflow fasta_gtf_bam_rpbp", "target_idx": 3}
{"id": "qc_adapt_bulk_multiqc_0_18", "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": "pipe_all101_viralmetagenome_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: 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": {"createpanelrefs": null, "spatialaxe": null, "pangenome": null, "variantprioritization": null, "multiplesequencealign": null, "hicar": null, "viralmetagenome": null, "slamseq": null, "detaxizer": null, "pathogensurveillance": null}}, "target": "viralmetagenome", "target_idx": 6}
{"id": "mod_plink2_vcf_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Import variant genetic data using plink2 (tools: plink2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"plink2_filter": "Filters plink bfiles or pfiles with filters such as maf or var", "scoary": "Use pangenome outputs for GWAS", "plink2_vcf": "Import variant genetic data using plink2", "biobambam_bammerge": "Merge a list of sorted bam files", "plink2_pmerge": "Merge a second PLINK 2 fileset into the first and write a new combined PLINK 2 fileset"}}, "target": "plink2_vcf", "target_idx": 2}
{"id": "mod_fibertoolsrs_extract_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Extract Fiber-seq information (such as m6A, CpG, nucleosomes, and MSPs) from BAM file into BED file (tools: fibertoolsrs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bismark_align": "Performs alignment of BS-Seq reads using bismark", "hmmer_hmmrank": "R script that scores output from multiple runs of hmmer/hmmsearch", "genmod_compound": "Score compounds", "bismark_genomepreparation": "Converts a specified reference genome into two different bisulfite\nconverted versions and indexes them for ali", "fibertoolsrs_extract": "Extract Fiber-seq information (such as m6A, CpG, nucleosomes, and MSPs) from BAM file into BED file"}}, "target": "fibertoolsrs_extract", "target_idx": 4}
{"id": "schema_std_mag_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/mag. Description: Assembly and binning of metagenomes.", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/mag.", "criteria": {"sample,run,group,short_reads_1,short_reads_2": null, "sample_id,img_directory,parameter_file": null, "fastq_1,fastq_2,batch,amp_batches,seq_batches": null, "sample,seed": null}}, "target": "sample,run,group,short_reads_1,short_reads_2", "target_idx": 0}
{"id": "resource_angsd_realsfs_0", "category": "resource_profiling", "state": {"process": "ANGSD_REALSFS", "tool": "angsd/realsfs", "description": "Estimate site frequency spectrum from site allele frequencies"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ANGSD_REALSFS (Estimate site frequency spectrum from site allele frequencies) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_low": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "qc_adapt_illumina_novaseq_2_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": "Evaluate the quality control tool choice for: Illumina NovaSeq X paired-end 150bp WGS (short_reads_150bp).", "criteria": {"Drop FastQC": null, "Swap for NanoPlot": null, "Keep FastQC": null}}, "target": "Keep FastQC", "target_idx": 2}
{"id": "mod_stitch_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: STITCH is an R program for reference panel free, read aware, low coverage sequencing genotype imputation. STITCH runs on a set of samples with sequencing reads in BAM format, as well as a list of positions to genotype, and outputs imputed genotypes in VCF format. (tools: stitch)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"stitch": "STITCH is an R program for reference panel free, read aware, low coverage sequencing genotype imputation. STIT", "gridss/generateponbedpe": "GRIDSS is a module software suite containing tools useful for the detection of genomic rearrangements.", "glimpse/chunk": "Defines chunks where to run imputation", "scoary": "Use pangenome outputs for GWAS", "glimpse/phase": "main GLIMPSE algorithm, performs phasing and imputation refining genotype likelihoods"}}, "target": "stitch", "target_idx": 0}
{"id": "mod_bed_scatter_bedtools_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Scatters inputted BED files by the amount specified.\nThe configuration in nextflow.config should be added to your modules.config for the subworkflow to work. (tools: bed_scatter_bedtools)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"bed_scatter_bedtools": null, "octopusv_stat": null, "bedgovcf": null, "agat_convertgff2bed": null, "whamg": null}}, "target": "bed_scatter_bedtools", "target_idx": 0}
{"id": "mod_gapseq_findtransport_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Predict transporters from genomic data using gapseq (tools: gapseq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gapseq/findtransport": null, "agat/spmergeannotations": null, "alignoth": null, "deacon/indexunion": null, "varlociraptor/filterfdr": null}}, "target": "gapseq/findtransport", "target_idx": 0}
{"id": "qc_adapt_singlecell_multiqc_1_9", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Keep FastQC": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "mod_gatk4_learnreadorientationmodel_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Uses f1r2 counts collected during mutect2 to Learn the prior probability of read orientation artifacts (tools: gatk4)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"gatk4_learnreadorientationmodel": "Uses f1r2 counts collected during mutect2 to Learn the prior probability of read orientation artifacts", "pyrodigal": "Pyrodigal is a Python module that provides bindings to Prodigal, a fast, reliable protein-coding gene predicti", "gatk4_printreads": "Print reads in the SAM/BAM/CRAM file", "gatk4_annotateintervals": "Annotates intervals with GC content, mappability, and segmental-duplication content", "gatk4_baserecalibrator": "Generate recalibration table for Base Quality Score Recalibration (BQSR)"}}, "target": "gatk4_learnreadorientationmodel", "target_idx": 0}
{"id": "samplesheet_arch_cageseq_transcription_1_3", "category": "samplesheet_schema", "state": {"assay": "CAGE-seq 5-prime capped transcript end sequencing", "first_step": "FASTQC", "inputs": "Single-end capped 5-prime cDNA tags for transcription start site (TSS) mapping"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for CAGE-seq 5-prime capped transcript end sequencing?", "criteria": {"sample,fastq_1": null, "sample,tss_bed": null, "sample,vcf": null, "sample,bam": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "resource_atlas_call_0", "category": "resource_profiling", "state": {"process": "ATLAS_CALL", "tool": "atlas/call", "description": "generate VCF file from a BAM file using various calling methods"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ATLAS_CALL (generate VCF file from a BAM file using various calling methods) in conf/base.config?", "criteria": {"process_single": null, "process_low": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_agat_spfilterfeaturefromkilllist_1", "category": "resource_profiling", "state": {"process": "AGAT_SPFILTERFEATUREFROMKILLLIST", "tool": "agat/spfilterfeaturefromkilllist", "description": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID.\nIf the feature has an ID (case insensitive) listed among the kill list it will be removed. /!\\ Removing a level1\nor level2 feature will automatically remove all linked subfeatures, and removing all children of a feature will\nautomatically remove this feature too."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to AGAT_SPFILTERFEATUREFROMKILLLIST (The script aims to remove features based on a kill list. The default behaviour i) in conf/base.config?", "criteria": {"process_high": null, "process_single": null, "process_medium": null, "process_low": null}}, "target": "process_single", "target_idx": 1}
{"id": "qc_adapt_qc_aggregate_2_13", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Multi-sample QC aggregation and reporting (multiqc_report).", "criteria": {"Drop MultiQC": null, "Swap for NanoPlot": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "pipe_all101_taxprofiler_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for classification analysis? Specific context: 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": {"callingcards": "A pipeline for processing calling cards data", "ampliseq": "Amplicon sequencing analysis workflow using DADA2 and QIIME2 [16s, 18s, amplicon-sequencing]", "funcscan": "(Meta-)genome screening for functional and natural product gene sequences [amp, amr, antibiotic-resistance]", "taxprofiler": "Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data [classification, illumina", "mag": "Assembly and binning of metagenomes [annotation, assembly, binning]"}}, "target": "taxprofiler", "target_idx": 3}
{"id": "pipe_all101_coproid_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Coprolite host Identification pipeline. Topics: adna, ancient-dna, coprolite, microbiome. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"sarek": "Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / tar", "methylseq": "Methylation (Bisulfite-Sequencing) analysis pipeline using Bismark/bwa-meth + MethylDackel or bwa-mem + rastair [bisulfi", "raredisease": "Call and score variants from WGS/WES of rare disease patients. [diagnostics, rare-disease, snv]", "detaxizer": "A pipeline to identify (and remove) certain sequences from raw genomic data. Default taxon to identify (and remove) is H", "coproid": "Coprolite host Identification pipeline [adna, ancient-dna, coprolite]"}}, "target": "coproid", "target_idx": 4}
{"id": "resource_bedtools_closest_1", "category": "resource_profiling", "state": {"process": "BEDTOOLS_CLOSEST", "tool": "bedtools/closest", "description": "For each feature in A, finds the closest feature (upstream or downstream) in B."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BEDTOOLS_CLOSEST (For each feature in A, finds the closest feature (upstream or downstream) in B.) in conf/base.config?", "criteria": {"process_long": null, "process_high": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "resource_bismark_summary_4", "category": "resource_profiling", "state": {"process": "BISMARK_SUMMARY", "tool": "bismark/summary", "description": "Uses Bismark report files of several samples in a run folder to generate a graphical summary HTML report."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BISMARK_SUMMARY (Uses Bismark report files of several samples in a run folder to generate a graph) in conf/base.config?", "criteria": {"process_medium": null, "process_single": null, "process_long": null, "process_high": null}}, "target": "process_single", "target_idx": 1}
{"id": "mod_mafft_align_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Multiple sequence alignment using MAFFT (tools: mafft)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mindagap_duplicatefinder": null, "any2fasta": null, "abritamr_run": null, "agat_spmergeannotations": null, "mafft_align": null}}, "target": "mafft_align", "target_idx": 4}
{"id": "mod_mmseqs_easycluster_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Cluster sequences using MMSeqs2 easy cluster. (tools: mmseqs)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"mmseqs/easysearch": "Searches for the sequences of a fasta file in a database using MMseqs2", "mmseqs/easycluster": "Cluster sequences using MMSeqs2 easy cluster.", "sourmash/pairwise": "Fast, multithreaded comparison of many FracMinHash signatures generated by sourmash sketch.", "mmseqs/createindex": "Creates sequence index for mmseqs database", "gem2/gemindexer": "Create a GEM index from a FASTA file"}}, "target": "mmseqs/easycluster", "target_idx": 1}
{"id": "schema_std_epitopeprediction_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/epitopeprediction", "description": "A bioinformatics best-practice analysis pipeline for epitope prediction and annotation", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/epitopeprediction?", "criteria": {"sample,fastq_1,fastq_2,strandedness": null, "sample,sample_id,fastq_1,fastq_2,method": null, "sample,type,level,msfile": null, "sample,alleles,mhc_class,filename": null}}, "target": "sample,alleles,mhc_class,filename", "target_idx": 3}
{"id": "qc_adapt_bulk_multiqc_0_5", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "For High-throughput bulk WGS multi-sample run, what is the recommended QC default for MultiQC?", "criteria": {"Keep FastQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null, "Drop MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 1}
{"id": "samplesheet_arch_rare_disease_trio_6_5", "category": "samplesheet_schema", "state": {"assay": "Trio exome/genome sequencing (Proband, Mother, Father)", "first_step": "FASTQC", "inputs": "Paired-end FASTQs with pedigree relationships and affected status"}, "question": {"type": "choice", "instructions": "Which columns are standard for Trio exome/genome sequencing (Proband, Mother, Father) input samplesheet?", "criteria": {"sample,bam,bai": null, "patient,sample,status,fastq_1,fastq_2": null, "family_id,sample,fastq_1,fastq_2": null, "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2": null}}, "target": "family_id,sample,paternal_id,maternal_id,sex,phenotype,fastq_1,fastq_2", "target_idx": 3}
{"id": "pipe_all101_viralmetagenome_0", "category": "pipeline_routing", "state": "I need to run an end-to-end bioinformatics workflow to analyze A nf-core pipeline for untargeted whole genome reconstruction with iSNV detection from metagenomic samples.. Topics: epidemiology, fastq, ngs, viral-metagenomics, virology, virus-genomes. . Which nf-core pipeline should I execute?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"pathogensurveillance": null, "magmap": null, "atacseq": null, "drop": null, "bactmap": null, "genomeqc": null, "viralmetagenome": null, "diaproteomics": null, "scnanoseq": null, "cageseq": null}}, "target": "viralmetagenome", "target_idx": 6}
{"id": "intent_debug_error_18", "category": "intent_routing", "state": "Classify this user request: \"My run failed with: Process `NFCORE_RNASEQ:RNASEQ:FASTQC (sample1)` terminated with an error exit status (137)\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules", "debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash"}}, "target": "debug_error", "target_idx": 3}
{"id": "noul_file_pairing_in_channel_tuples_19", "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": "intent_ask_question_0", "category": "intent_routing", "state": "Classify this user request: \"What is the difference between path and file qualifiers in Nextflow DSL2 input blocks?\"", "question": {"type": "choice", "instructions": "Classify the user intent into one category.", "criteria": {"debug_error": "User is reporting a runtime error, exit code (137, 127), task failure, or pipeline crash", "build_pipeline": "User wants to generate, assemble, compose, or write a Nextflow pipeline, workflow, or DAG", "prepare_data": "User needs help creating a samplesheet, parsing FASTQ/BAM filenames, or staging reference genomes", "ask_question": "User is asking for an explanation, conceptual difference, documentation, or Nextflow syntax rules"}}, "target": "ask_question", "target_idx": 3}
{"id": "field_constraint_bai_3_2", "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, "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$": null, "type: boolean": null}}, "target": "pattern: ^\\S+\\.bam\\.bai$ or ^\\S+\\.bai$", "target_idx": 2}
{"id": "mod_rclone_checksum_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Check files in a destination path against a checksum SUM file (tools: rclone)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rclone_copy": "Copy files or directories between local and/or remote storage using Rclone", "blast_blastn": "Queries a BLAST DNA database", "rclone_checksum": "Check files in a destination path against a checksum SUM file", "genrich": "Peak-calling for ChIP-seq and ATAC-seq enrichment experiments", "md5sum": "Create MD5 (128-bit) checksums"}}, "target": "rclone_checksum", "target_idx": 2}
{"id": "field_constraint_sample_0_3", "category": "samplesheet_schema", "state": {"field_name": "sample", "datatype": "unique_identifier", "description": "Sample identifier across all nf-core pipelines"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'sample'?", "criteria": {"enum: [0, 1]": null, "format: file-path": null, "type: integer": null, "pattern: ^\\S+$ (no whitespace, unique)": null}}, "target": "pattern: ^\\S+$ (no whitespace, unique)", "target_idx": 3}
{"id": "mod_gtdbtk_gtdbtoncbimajorityvote_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Converts the output classifications of GTDB-TK from GTDB taxonomy to NCBI taxonomy (tools: gtdbtk)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"odgi_viz": null, "catpack_download": null, "gtdbtk_gtdbtoncbimajorityvote": null, "taxpasta_merge": null, "catpack_reads": null}}, "target": "gtdbtk_gtdbtoncbimajorityvote", "target_idx": 2}
{"id": "mod_tinc_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: TINC is a package to determine the contamination of tumour DNA in a matched normal sample. The approach uses evolutionary theory applied to read counts data from whole-genome sequencing assays. (tools: tinc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"tinc": "TINC is a package to determine the contamination of tumour DNA in a matched normal sample. The approach uses e", "mmseqs/tsv2exprofiledb": "Conversion of expandable profile to databases to the MMseqs2 databases format", "agat/spfilterfeaturefromkilllist": "The script aims to remove features based on a kill list. The default behaviour is to look at the features's ID", "samtools/index": "Index SAM/BAM/CRAM file", "alignoth": "Creating alignment plots from bam files"}}, "target": "tinc", "target_idx": 0}
{"id": "local_subworkflow_nextclade_2_2", "category": "subworkflow_packaging", "state": {"subworkflow": "NEXTCLADE", "modules": ["nextclade/run"], "description": "Viral clade typing and QC"}, "question": {"type": "choice", "instructions": "Determine the DSL2 structure for NEXTCLADE (nextclade/run).", "criteria": {"Leave them out": null, "Local subworkflow NEXTCLADE": null, "Use nf-core subworkflow nextclade": null, "Keep the modules in the main workflow": null}}, "target": "Local subworkflow NEXTCLADE", "target_idx": 1}
{"id": "qc_adapt_qc_aggregate_1_40", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Swap for NanoPlot": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "qc_adapt_pe_illumina_fastqc_2_21", "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": "pipe_all101_detaxizer_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: A pipeline to identify (and remove) certain sequences from raw genomic data. Default taxon to identify (and remove) is Homo sapiens. Removal is optional.. Topics: de-identification, decontamination, edna, fastq, filter, long-reads. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"viralintegration": "Analysis pipeline for the identification of viral integration events in genomes using a chimeric read approach. [chimeri", "readsimulator": "A pipeline to simulate sequencing reads, such as Amplicon, Target Capture, Metagenome, and Whole genome data. ", "eager": "A fully reproducible and state-of-the-art ancient DNA analysis pipeline [adna, ancient-dna-analysis, ancientdna]", "detaxizer": "A pipeline to identify (and remove) certain sequences from raw genomic data. Default taxon to identify (and remove) is H", "differentialabundance": "Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq  [atac-seq, chip-seq, d", "spatialaxe": "A bioinformatics best-practice processing and quality control pipeline for Xenium and Artera data [10x-genomics, atera, ", "kmermaid": " k-mer similarity analysis pipeline [k-mer, kmer, kmer-counting]", "pathogensurveillance": "Surveillance of pathogens using population genomics and sequencing [biosurveillance, pathogen-identification]"}}, "target": "detaxizer", "target_idx": 3}
{"id": "mod_utils_nfvalidation_plugin_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Use nf-validation to initiate and validate a pipeline (tools: utils_nfvalidation_plugin)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"utils_nextflow_pipeline": "Subworkflow with functionality that may be useful for any Nextflow pipeline", "prinseqplusplus": "PRINSEQ++ is a C++ implementation of the prinseq-lite.pl program. It can be used to filter, reformat or trim g", "openms_psmfeatureextractor": "Computes extra features for each input PSM for use with Percolator rescoring.", "utils_nfcore_pipeline": "Subworkflow with utility functions specific to the nf-core pipeline template", "utils_nfvalidation_plugin": "Use nf-validation to initiate and validate a pipeline"}}, "target": "utils_nfvalidation_plugin", "target_idx": 4}
{"id": "samplesheet_arch_ont_metagenome_single_0_1", "category": "samplesheet_schema", "state": {"assay": "Long-read Oxford Nanopore environmental metagenomic sequencing", "first_step": "NANOPLOT", "inputs": "High molecular weight environmental metagenomic long reads per sampling site"}, "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have for: Long-read Oxford Nanopore environmental metagenomic sequencing?", "criteria": {"sample,fastq_1,group": null, "sample,fastq_1": null, "sample,fasta": null, "sample,bam": null}}, "target": "sample,fastq_1,group", "target_idx": 0}
{"id": "subworkflow_pkg_fastq_complexity_filter_0", "category": "subworkflow_packaging", "state": {"subworkflow": "FASTQ_COMPLEXITY_FILTER", "modules": ["prinseqplusplus", "bbmap/bbduk", "fastp"], "description": "Perform low-complexity filtering of FASTQ reads using a selectable tool."}, "question": {"type": "choice", "instructions": "How should FASTQ_COMPLEXITY_FILTER (prinseqplusplus, bbmap/bbduk, fastp) be structured in DSL2?", "criteria": {"Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow fastq_complexity_filter": null, "Local subworkflow FASTQ_COMPLEXITY_FILTER": null}}, "target": "Use nf-core subworkflow fastq_complexity_filter", "target_idx": 2}
{"id": "mod_bamaligncleaner_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: removes unused references from header of sorted BAM/CRAM files. (tools: bamaligncleaner)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"custom_clustermetrics": null, "ascat": null, "bamreadcount": null, "fastqscreen_buildfromindex": null, "bamaligncleaner": null}}, "target": "bamaligncleaner", "target_idx": 4}
{"id": "pipe_all101_hicar_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: Pipeline for HiCAR data, a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chromatin accessibility and cis-regulatory chromatin contacts.. Topics: atac, atac-seq, hic, hicar, multi-omics, transcriptome. ?", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"viralrecon": "Assembly and intrahost/low-frequency variant calling for viral samples [amplicon, artic, assembly]", "hicar": "Pipeline for HiCAR data, a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chrom", "callingcards": "A pipeline for processing calling cards data", "hgtseq": "A pipeline to investigate horizontal gene transfer from NGS data [bwa-mem, bwa-mem2, fastqc]", "pacvar": "Longread PacBio sequencing processing for WGS and PureTarget [alignment, long-read, pacbio]"}}, "target": "hicar", "target_idx": 1}
{"id": "samplesheet_arch_smartseq_plate_based_6_0", "category": "samplesheet_schema", "state": {"technology": "Single-Cell Genomics", "workflow_entry": "FASTQC", "library_inputs": "Full-length transcript cDNA FASTQs sorted across 96-well or 384-well plates"}, "question": {"type": "choice", "instructions": "Which columns are standard for Smart-seq2 / Smart-seq3 plate-based full-length single-cell RNA-seq input samplesheet?", "criteria": {"sample,well,fastq": null, "plate,well,sample,fastq_1,fastq_2": null, "sample,fastq_1,fastq_2": null, "plate,sample,bam": null}}, "target": "plate,well,sample,fastq_1,fastq_2", "target_idx": 1}
{"id": "samplesheet_arch_pacbio_hifi_unaligned_bam_5_3", "category": "samplesheet_schema", "state": {"assay": "PacBio HiFi unaligned BAM variant calling", "first_step": "PBMM2_ALIGN", "inputs": "Native unaligned PacBio Sequel IIe / Revio BAM containing kinetics and qualities"}, "question": {"type": "choice", "instructions": "In Nextflow pipeline nf-core/pacvar, determine the input samplesheet column structure for: PacBio HiFi unaligned BAM variant calling.", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fastq_1": null, "sample,bam": null, "sample,vcf": null}}, "target": "sample,bam", "target_idx": 2}
{"id": "mod_mosdepth_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Calculates genome-wide sequencing coverage. (tools: mosdepth)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ascat": "copy number profiles of tumour cells.", "bamclipper": "This module is used to clip primer sequences from your alignments.", "mcstaging_macsima2mc": "Staging module for MCMICRO transforming MACSima data sets for being registered with ASHLAR in MCMICRO.", "bcftools_query": "Extracts fields from VCF or BCF files and outputs them in user-defined format.", "mosdepth": "Calculates genome-wide sequencing coverage."}}, "target": "mosdepth", "target_idx": 4}
{"id": "resource_ashlar_5", "category": "resource_profiling", "state": {"process": "ASHLAR", "tool": "ashlar", "description": "Alignment by Simultaneous Harmonization of Layer/Adjacency Registration"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to ASHLAR (Alignment by Simultaneous Harmonization of Layer/Adjacency Registration) in conf/base.config?", "criteria": {"process_medium": null, "process_high": null, "process_single": null, "process_low": null}}, "target": "process_single", "target_idx": 2}
{"id": "resource_blast_tblastn_3", "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_low": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_rseqc_inferexperiment_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Infer strandedness from sequencing reads (tools: rseqc)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ctatsplicing_prepgenomelib": null, "arcane_filter": null, "rseqc_inferexperiment": null, "plink_bmerge": null, "pychopper": null}}, "target": "rseqc_inferexperiment", "target_idx": 2}
{"id": "mod_centrifuger_build_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Build centrifuger database for taxonomic profiling (tools: centrifuger)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"biomformat_convert": "Convert biom table to different format.\nConversion between text tab-delimited, BIOM-v1 (JSON), and BIOM-v2 (HD", "octopusv_svcf2bed": "Converts octopusv SVCF files to the standard BED format", "binette": "A fast and accurate binning refinement tool to construct high quality MAGs from the output of multiple binning", "spaceranger_count": "Module to use the 10x Space Ranger pipeline to process 10x spatial transcriptomics data", "centrifuger_build": "Build centrifuger database for taxonomic profiling"}}, "target": "centrifuger_build", "target_idx": 4}
{"id": "qc_adapt_qc_aggregate_2_29", "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": "qc_adapt_ont_ultra_long_1_28", "category": "qc_read_adaptation", "state": {"assay": "Ultra-long Oxford Nanopore genomic DNA reads", "tool": "FastQC", "read_type": "long_reads_20kb_plus"}, "question": {"type": "choice", "instructions": "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_krakenuniq_download_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Download KrakenUniq databases and related fles (tools: krakenuniq)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD).", "pharmcat/reporter": "The Reporter module is responsible for generating a report with genotype-specific\nexpert-reviewed drug prescri", "krakenuniq/download": "Download KrakenUniq databases and related fles", "amps": "Post-processing script of the MaltExtract component of the HOPS package", "srst2/srst2": "Short Read Sequence Typing for Bacterial Pathogens is a program designed to take Illumina sequence data,\na MLS"}}, "target": "krakenuniq/download", "target_idx": 2}
{"id": "mod_rclone_copy_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Copy files or directories between local and/or remote storage using Rclone (tools: rclone)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"rclone_checksum": null, "regenie_runl1": null, "rclone_copy": null, "pairtools_flip": null, "rclone_check": null}}, "target": "rclone_copy", "target_idx": 2}
{"id": "pipe_all101_seqinspector_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: Dedicated QC-only pipeline for sequencing data. The pipeline will run a (potentially large) set of QC tools and can output global and group specific Multiqc reports. The pipeline is targeting core facilities or research groups with larger sequencing throughput.. Topics: genomics, quality-control. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"eager": null, "marsseq": null, "reportho": null, "seqinspector": null, "lsmquant": null}}, "target": "seqinspector", "target_idx": 3}
{"id": "qc_adapt_targeted_amplicon_2_9", "category": "qc_read_adaptation", "state": {"assay": "Targeted Illumina amplicon panel", "tool": "FastQC", "read_type": "short_reads_pe250"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: Targeted Illumina amplicon panel (short_reads_pe250).", "criteria": {"Drop FastQC": null, "Keep FastQC": null, "Swap for NanoPlot": null}}, "target": "Keep FastQC", "target_idx": 1}
{"id": "samplesheet_arch_prealigned_bam_indexed_1_0", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/sarek) for Pre-aligned BAM variant calling pipeline. Input files: Aligned BAM files.", "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for Pre-aligned BAM variant calling pipeline?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,bam,bai": null, "sample,fastq_1": null, "sample,bam": null}}, "target": "sample,bam,bai", "target_idx": 1}
{"id": "mod_suppa_diffsplice_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Perform differential splicing analysis using SUPPA. (tools: suppa)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"leafcutter/differentialsplicing": null, "ensemblvep/download": null, "suppa/clusterevents": null, "suppa/diffsplice": null, "hisat3n/build": null}}, "target": "suppa/diffsplice", "target_idx": 3}
{"id": "mod_hamronization_rgi_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Tool to convert and summarize RGI outputs using the hAMRonization specification. (tools: hamronization)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"argnorm": "Normalize antibiotic resistance genes (ARGs) using the ARO ontology (developed by CARD).", "atlas_splitmerge": "split single end read groups by length and merge paired end reads", "trtools_dumpstr": "DumpSTR filters VCF files with TR genotypes, performing call-level and locus-level filtering, and outputs a fi", "hamronization_amrfinderplus": "Tool to convert and summarize AMRfinderPlus outputs using the hAMRonization specification.", "hamronization_rgi": "Tool to convert and summarize RGI outputs using the hAMRonization specification."}}, "target": "hamronization_rgi", "target_idx": 4}
{"id": "mod_methurator_plot_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Plots results produced by methurator gtestimator. (tools: methurator)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"methurator/gtestimator": "Run estimator for DNA methylation sequencing saturation.", "hifiadapterfilt/downloaddb": "Downloads the pre-built PacBio adapter BLAST database from the HiFiAdapterFilt\nGitHub repository. The database", "paraclu": "Paraclu finds clusters in data attached to sequences.", "methurator/plot": "Plots results produced by methurator gtestimator.", "bismark/align": "Performs alignment of BS-Seq reads using bismark"}}, "target": "methurator/plot", "target_idx": 3}
{"id": "mod_mapdamage2_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Computational framework for tracking and quantifying DNA damage patterns among ancient DNA sequencing reads generated by Next-Generation Sequencing platforms. (tools: mapdamage2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"endorspy": "endorS.py calculates endogenous DNA from samtools flagstat files and print to screen", "mapdamage2": "Computational framework for tracking and quantifying DNA damage patterns among ancient DNA sequencing reads ge", "atlas_pmd": "Estimate the post-mortem damage patterns of DNA", "faa_seqfu_seqkit": "Subworkflow that optionally preprocesses amino acid FASTA sequences\n(seqkit seq/replace/rmdup), computes seque", "megahit": "An ultra-fast metagenomic assembler for large and complex metagenomics"}}, "target": "mapdamage2", "target_idx": 1}
{"id": "pipe_all101_cageseq_4", "category": "pipeline_routing", "state": "Which pipeline implements best-practice processing for: 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": {"proteogenomicsdb": "The ProteoGenomics database generation workflow creates different protein databases for ProteoGenomics data analysis. [c", "metapep": "From metagenomes to epitopes and beyond", "viralintegration": "Analysis pipeline for the identification of viral integration events in genomes using a chimeric read approach. [chimeri", "magmap": "Best-practice analysis pipeline for mapping reads to a (large) collections of genomes", "cageseq": "CAGE-sequencing analysis pipeline with trimming, alignment and counting of CAGE tags. [cage, cage-seq, cageseq-data]", "nascent": "Nascent Transcription Processing Pipeline [gro-seq, nascent, pro-seq]", "pairgenomealign": "Pairwise genome comparison pipeline using the LAST software to align a list of query genomes to a target genome, and plo", "proteinfold": "Protein 3D structure prediction pipeline [alphafold2, colabfold, esmfold]", "longraredisease": "Long read sequencing pipeline to identify variants in patients with neurodevelopmental disorders  [nanopore, pacbio]", "lsmquant": "A pipeline for processing and analysis of light-sheet microscopy images. [3dunet, image-analysis, image-processing]"}}, "target": "cageseq", "target_idx": 4}
{"id": "subworkflow_pkg_fasta_index_bismark_bwameth_1", "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": {"Leave them out": null, "Keep the modules in the main workflow": null, "Use nf-core subworkflow fasta_index_bismark_bwameth": null, "Local subworkflow FASTA_INDEX_BISMARK_BWAMETH": null}}, "target": "Use nf-core subworkflow fasta_index_bismark_bwameth", "target_idx": 2}
{"id": "noul_container_environment_specification_24", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"DSL2 `container` directives can specify Docker, Singularity, or Wave containers per process.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_abacas_1", "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_convertbed2gff": "Takes a bed12 file and converts to a GFF3 file", "qsv_cat": "Concatenate two or more CSV (or TSV) tables into a single table", "bedtools_shuffle": "bedtools shuffle will randomly permute the genomic locations of a feature file among a genome defined in a gen", "abyss_abysspe": "ABySS is a de novo sequence assembler intended for short paired-end reads and genomes of all sizes.", "abacas": "Contiguate draft genome assembly"}}, "target": "abacas", "target_idx": 4}
{"id": "qc_adapt_bulk_multiqc_2_6", "category": "qc_read_adaptation", "state": {"assay": "High-throughput bulk WGS multi-sample run", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "Evaluate the quality control tool choice for: High-throughput bulk WGS multi-sample run (summary_reporting).", "criteria": {"Keep FastQC": null, "Drop MultiQC": null, "Keep MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "field_constraint_strandedness_0_10", "category": "samplesheet_schema", "state": {"field_name": "strandedness", "datatype": "categorical_enum", "description": "Library strandedness orientation in RNA-seq protocols"}, "question": {"type": "choice", "instructions": "What is the JSON Schema validation constraint for samplesheet column 'strandedness'?", "criteria": {"format: file-path": null, "pattern: ^[0-9]+$": null, "type: boolean": null, "enum: [auto, forward, reverse, unstranded]": null}}, "target": "enum: [auto, forward, reverse, unstranded]", "target_idx": 3}
{"id": "qc_adapt_illumina_novaseq_2_12", "category": "qc_read_adaptation", "state": {"assay": "Illumina NovaSeq X paired-end 150bp WGS", "tool": "FastQC", "read_type": "short_reads_150bp"}, "question": {"type": "choice", "instructions": "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": "field_constraint_phenotype_2_0", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'phenotype' (Affection status in clinical trio / family analysis) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'phenotype' validated?", "criteria": {"enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null, "type: string free-text": null, "format: file-path": null, "enum: [normal, tumor]": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 0}
{"id": "noul_channel_mix_operator_22", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.mix()` combines two or more channels of identical emission structure into a single unified stream.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards.", "criteria": {"false": "The statement describes an invalid Nextflow DSL2 syntax, anti-pattern, or deprecated behavior.", "true": "The statement describes a valid, standard, and recommended Nextflow DSL2 practice."}, "labels": {"false": "Invalid / Anti-pattern", "true": "Valid / Recommended"}}, "target": "true", "target_idx": 1}
{"id": "mod_chromap_chromap_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Performs preprocessing and alignment of chromatin fastq files to fasta reference files using chromap. (tools: chromap)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amps": "Post-processing script of the MaltExtract component of the HOPS package", "basicpy": "BaSiCPy is a python package for background and shading correction of optical microscopy images. It is develope", "chromap/chromap": "Performs preprocessing and alignment of chromatin fastq files to fasta reference files using chromap.", "purgedups/purgedups": "Purge haplotigs and overlaps for an assembly", "abra2": "Assembly Based ReAligner for next-generation sequencing data"}}, "target": "chromap/chromap", "target_idx": 2}
{"id": "mod_gcta_addgrms_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Combine multiple GRMs listed in an MGRM manifest into a single dense GRM (tools: gcta)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"saltshaker/plot": "mtDNA deletion and duplication plotting downstream of mitosalt", "gcta/grmcutoff": "Apply a genetic relationship cutoff to a dense GRM using `gcta --grm-cutoff`", "duckdb/table2parquet": "Convert a delimited text table (CSV or TSV, gzipped or not) to Parquet", "gcta/addgrms": "Combine multiple GRMs listed in an MGRM manifest into a single dense GRM", "gcta/adjustgrm": "Adjust a dense GRM for incomplete tagging using `gcta --grm-adj`"}}, "target": "gcta/addgrms", "target_idx": 3}
{"id": "samplesheet_arch_viral_amplicon_artic_2_2", "category": "samplesheet_schema", "state": "Building an autonomous Nextflow workflow (nf-core/viralrecon) for Viral amplicon sequencing with primers. Input files: Paired-end tiled viral amplicon FASTQs per clinical swab sample.", "question": {"type": "choice", "instructions": "Which columns should the input samplesheet have?", "criteria": {"sample,fastq_1,fastq_2": null, "sample,fasta": null, "sample,vcf": null, "sample,fastq_1": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 0}
{"id": "pipe_all101_dualrnaseq_1", "category": "pipeline_routing", "state": "User query: What is the official nf-core pipeline for dualrna-seq analysis? Specific context: Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous RNA-seq.. Topics: dualrna-seq, host-pathogen, quantification, readmapping, rna-seq. ", "question": {"type": "choice", "instructions": "Select the optimal nf-core pipeline for this bioinformatic analysis task.", "criteria": {"nanoseq": "Nanopore demultiplexing, QC and alignment pipeline [alignment, demultiplexing, nanopore]", "rnasplice": "rnasplice is a bioinformatics pipeline for RNA-seq alternative splicing analysis [alternative-splicing, rna, rna-seq]", "dualrnaseq": "Analysis of Dual RNA-seq data - an experimental method for interrogating host-pathogen interactions through simultaneous", "rnaseq": "RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality contr", "funcprofiler": "Read-based functional profiling of microbiome sequencing data"}}, "target": "dualrnaseq", "target_idx": 2}
{"id": "mod_happy_prepy_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Pre.py is a preprocessing tool made to preprocess VCF files for Hap.py (tools: happy)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"happy/prepy": "Pre.py is a preprocessing tool made to preprocess VCF files for Hap.py", "pbsv/discover": "pbsv - PacBio structural variant (SV) signature discovery tool", "gatk4/haplotypecaller": "Call germline SNPs and indels via local re-assembly of haplotypes", "hamronization/deeparg": "Tool to convert and summarize DeepARG outputs using the hAMRonization specification", "happy/sompy": "Hap.py is a tool to compare diploid genotypes at haplotype level. som.py is a part of hap.py compares somatic "}}, "target": "happy/prepy", "target_idx": 0}
{"id": "mod_magus_align_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Multiple Sequence Alignment using Graph Clustering (tools: magus)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"clustalo/align": null, "famsa/align": null, "magus/align": null, "vcf2cytosure": null, "vrhyme/linkbins": null}}, "target": "magus/align", "target_idx": 2}
{"id": "mod_dysgu_run_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Dysgu calls structural variants (SVs) from mapped sequencing reads. It is designed for accurate and efficient detection of structural variations. (tools: dysgu)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ariba_getref": "Download and prepare database for Ariba analysis", "dysgu_run": "Dysgu calls structural variants (SVs) from mapped sequencing reads. It is designed for accurate and efficient ", "gatk4_collectsvevidence": "Gathers paired-end and split read evidence files for use in the GATK-SV pipeline. Output files are a file cont", "gatk4_printsvevidence": "WARNING - this tool is still experimental and shouldn't be used in a production setting. Gathers paired-end an", "custom_orfnormalise": "Convert one ORF caller's per-sample output table into a unified BED12 plus a\nsidecar metadata TSV, ready for c"}}, "target": "dysgu_run", "target_idx": 1}
{"id": "noul_channel_operator_map_1", "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_scrna_10x_v3_0_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": "Which columns should the input samplesheet have for: Single-cell 10x Genomics 3-prime Gene Expression (v3 chemistry)?", "criteria": {"sample,matrix,barcodes,features": null, "sample,fastq_1,fastq_2,expected_cells": null, "sample,fastq_1": null, "sample,fastq_1,fastq_2": null}}, "target": "sample,fastq_1,fastq_2,expected_cells", "target_idx": 1}
{"id": "qc_adapt_bulk_multiqc_0_6", "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": "mod_ribocode_ribocode_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Call ORFs with RiboCode from Ribo-Seq data (tools: ribocode)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"ribocode/ribocode": "Call ORFs with RiboCode from Ribo-Seq data", "custom/orfmerge": "Cluster normalised per-sample, per-caller ORF predictions into a single\ncohort-level catalogue. Pair with `cus", "custom/orfnormalise": "Convert one ORF caller's per-sample output table into a unified BED12 plus a\nsidecar metadata TSV, ready for c", "umitools/prepareforrsem": "Make the output from umi_tools dedup or group compatible with RSEM", "rastair/methylkit": "Parses rastair call output and converts it into a MethylKit-compatible format."}}, "target": "ribocode/ribocode", "target_idx": 0}
{"id": "noul_executor_support_8", "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": "qc_adapt_qc_aggregate_1_35", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample QC aggregation and reporting", "tool": "MultiQC", "read_type": "multiqc_report"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: multiqc_report?", "criteria": {"Keep MultiQC": null, "Drop MultiQC": null, "Swap for NanoPlot": null}}, "target": "Keep MultiQC", "target_idx": 0}
{"id": "samplesheet_arch_metatranscriptome_denovo_4_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": "What samplesheet columns are expected when inputs are: Paired-end total RNA reads from complex microbial communities with ribosomal RNA filtering?", "criteria": {"sample,rrna_fasta": null, "sample,fastq_1": null, "sample,bam": null, "sample,fastq_1,fastq_2,environment": null}}, "target": "sample,fastq_1,fastq_2,environment", "target_idx": 3}
{"id": "mod_prodigal_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Prodigal (Prokaryotic Dynamic Programming Genefinding Algorithm) is a microbial (bacterial and archaeal) gene finding program (tools: prodigal)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"antismash_antismashdownloaddatabases": "antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynt", "glimpse2_splitreference": "Tool to create a binary reference panel for quick reading time.", "traitar_run": "Traitar3 - predict microbial phenotypes from genomic sequences using protein families", "prodigal": "Prodigal (Prokaryotic Dynamic Programming Genefinding Algorithm) is a microbial (bacterial and archaeal) gene ", "rtgtools_svdecompose": "The svdecompose tool of RTG tools. It is used to decompose structural variants to BNDs"}}, "target": "prodigal", "target_idx": 3}
{"id": "samplesheet_arch_viral_ont_single_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/viralrecon", "assay_type": "Viral genome sequencing on Oxford Nanopore MinION / GridION", "data_format": "Demultiplexed single-end long reads from tiled viral amplicons"}, "question": {"type": "choice", "instructions": "Which columns are standard for Viral genome sequencing on Oxford Nanopore MinION / GridION input samplesheet?", "criteria": {"sample,fastq_1": null, "sample,bam": null, "sample,vcf": null, "sample,fasta": null}}, "target": "sample,fastq_1", "target_idx": 0}
{"id": "noul_channel_mix_operator_3", "category": "dsl2_rules", "state": "Is this statement accurate according to standard Nextflow DSL2 behavior? \"Channel `.mix()` combines two or more channels of identical emission structure into a single unified stream.\"", "question": {"type": "noul", "instructions": "Determine whether the Nextflow DSL2 statement or idiom is valid and adheres to standards."}, "target": "true", "target_idx": 1}
{"id": "samplesheet_arch_bulk_wgs_pe_6_3", "category": "samplesheet_schema", "state": "nextflow run nf-core/sarek --input samplesheet.csv (Assay: Standard Paired-end Whole Genome Sequencing (WGS))", "question": {"type": "choice", "instructions": "Which columns are standard for Standard Paired-end Whole Genome Sequencing (WGS) input samplesheet?", "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,fastq_2", "target_idx": 0}
{"id": "resource_bigslice_downloaddb_3", "category": "resource_profiling", "state": {"process": "BIGSLICE_DOWNLOADDB", "tool": "bigslice/downloaddb", "description": "Downloads and extracts the BiG-SLiCE HMM database (biosynthetic and sub Pfams)\nusing the bundled `download_bigslice_hmmdb` script shipped with BiG-SLiCE.\nThe resulting directory can be passed directly as the `hmmdb` input to the\n`BIGSLICE` module."}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BIGSLICE_DOWNLOADDB (Downloads and extracts the BiG-SLiCE HMM database (biosynthetic and sub Pfams)\nu) in conf/base.config?", "criteria": {"process_long": null, "process_single": null, "process_high": null, "process_medium": null}}, "target": "process_single", "target_idx": 1}
{"id": "schema_std_tfactivity_0_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/tfactivity", "description": "Bioinformatics pipeline that makes use of expression and open chromatin data to identify differentially active transcription factors across conditions.", "mode": "standard_execution"}, "question": {"type": "choice", "instructions": "Which standard samplesheet columns are configured in assets/schema_input.json for nf-core/tfactivity?", "criteria": {"sample,condition,assay,peak_file,footprinting": null, "id,fasta,query": null, "sample,fastq_1,fastq_2,fastq_barcode,expected_cells": null, "patient,sample,vcf,status,cna": null}}, "target": "sample,condition,assay,peak_file,footprinting", "target_idx": 0}
{"id": "local_subworkflow_checkirma_1_1", "category": "subworkflow_packaging", "state": {"subworkflow": "CHECKIRMA", "modules": ["custom/checkirma"], "description": "Custom validation of assembly output"}, "question": {"type": "choice", "instructions": "How should this step (custom/checkirma) be packaged: Custom validation of assembly output?", "criteria": {"Local subworkflow CHECKIRMA": null, "Use nf-core subworkflow checkirma": null, "Leave them out": null, "Keep the modules in the main workflow": null}}, "target": "Local subworkflow CHECKIRMA", "target_idx": 0}
{"id": "field_constraint_phenotype_3_8", "category": "samplesheet_schema", "state": {"schema_target": "assets/schema_input.json", "field": "phenotype", "validation_type": "pedigree_phenotype_enum"}, "question": {"type": "choice", "instructions": "Select the appropriate draft-07 JSON Schema property specification for 'phenotype'.", "criteria": {"enum: [0, 1, 2, -9] (1=unaffected, 2=affected)": null, "format: file-path": null, "type: string free-text": null, "enum: [normal, tumor]": null}}, "target": "enum: [0, 1, 2, -9] (1=unaffected, 2=affected)", "target_idx": 0}
{"id": "resource_bamstats_generalstats_5", "category": "resource_profiling", "state": {"process": "BAMSTATS_GENERALSTATS", "tool": "bamstats/generalstats", "description": "write your description here"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BAMSTATS_GENERALSTATS (write your description here) in conf/base.config?", "criteria": {"process_single": null, "process_high": null, "process_low": null, "process_long": null}}, "target": "process_single", "target_idx": 0}
{"id": "resource_blat_3", "category": "resource_profiling", "state": {"process": "BLAT", "tool": "blat", "description": "Queries a sequence subject"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BLAT (Queries a sequence subject) in conf/base.config?", "criteria": {"process_long": null, "process_medium": null, "process_low": null, "process_single": null}}, "target": "process_single", "target_idx": 3}
{"id": "pipe_all101_riboseq_3", "category": "pipeline_routing", "state": "Recommend the most appropriate nf-core workflow for the following project: 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": {"spatialaxe": null, "bacass": null, "riboseq": null, "funcprofiler": null, "references": null}}, "target": "riboseq", "target_idx": 2}
{"id": "mod_bam_dedup_umi_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: BAM deduplication with UMI processing for both genome and transcriptome alignments (tools: bam_dedup_umi)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"porechop/abi": "Extension of Porechop whose purpose is to process adapter sequences in ONT reads.", "pairtools/dedup": "Find and remove PCR/optical duplicates", "bam_dedup_umi": "BAM deduplication with UMI processing for both genome and transcriptome alignments", "humid": "HUMID is a tool to quickly and easily remove duplicate reads from FASTQ files, with or without UMIs.", "juicertools/pre": "Create a multi-resolution .hic contact matrix for analysis with Juicer"}}, "target": "bam_dedup_umi", "target_idx": 2}
{"id": "field_constraint_fastq_2_2_2", "category": "samplesheet_schema", "state": "Validating samplesheet CSV field 'fastq_2' (Path to read 2 FASTQ file for paired-end sequencing) in assets/schema_input.json.", "question": {"type": "choice", "instructions": "In nf-core samplesheet schema (assets/schema_input.json), how is column 'fastq_2' validated?", "criteria": {"type: required string": null, "pattern: ^\\S+\\.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_faire_seq_chromatin_1_4", "category": "samplesheet_schema", "state": {"assay": "FAIRE-seq / DNAse-seq open chromatin profiling", "first_step": "FASTQC"}, "question": {"type": "choice", "instructions": "Which columns should the samplesheet have for FAIRE-seq / DNAse-seq open chromatin profiling?", "criteria": {"sample,fastq_1": null, "sample,bam,bai": null, "sample,fastq_1,fastq_2": null, "sample,vcf": null}}, "target": "sample,fastq_1,fastq_2", "target_idx": 2}
{"id": "mod_holodeck_mutate_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Generate a VCF of random mutations from a reference genome with holodeck (tools: holodeck)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"holodeck/mutate": "Generate a VCF of random mutations from a reference genome with holodeck", "gapseq/find": "Predict metabolic pathways from genomic data using gapseq", "rhocall/annotate": "Markup VCF file using rho-calls.", "survivor/simsv": "Simulate an SV VCF file based on a reference genome", "hmmer/hmmemit": "emit sequences from a profile HMM"}}, "target": "holodeck/mutate", "target_idx": 0}
{"id": "schema_std_tumourevo_2_1", "category": "samplesheet_schema", "state": "Configuring input samplesheet for nf-core pipeline nf-core/tumourevo. Description: Analysis pipeline to model tumour clonal evolution from WGS data (driver annotation, quality control of copy number calls, subclonal and mutational signature deconvolution).", "question": {"type": "choice", "instructions": "Define the input samplesheet column header for nf-core/tumourevo.", "criteria": {"patient,vcf,tbi,dataset,tumour_sample": null, "sample,fastq_1,fastq_2,bam,bai": null, "sample,run,group,short_reads_1,short_reads_2": null, "sample,alleles,mhc_class,filename": null}}, "target": "patient,vcf,tbi,dataset,tumour_sample", "target_idx": 0}
{"id": "mod_sylph_sketch_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Sketching/indexing sequencing reads (tools: sylph)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"skani_dist": "Simple ANI calculation between reference and query genomes.", "ska_fasta": "Create genome sketch using split k-mers", "purecn_coverage": "Calculate intervals coverage for each sample. N.B. the tool can not handle staging files with symlinks, stageI", "sylph_sketch": "Sketching/indexing sequencing reads", "tcoffee_seqreformat": "Reformats files with t-coffee"}}, "target": "sylph_sketch", "target_idx": 3}
{"id": "qc_adapt_singlecell_multiqc_1_41", "category": "qc_read_adaptation", "state": {"assay": "Multi-sample single-cell RNA-seq cohort", "tool": "MultiQC", "read_type": "summary_reporting"}, "question": {"type": "choice", "instructions": "How should QC step MultiQC be configured given sequencing characteristics: summary_reporting?", "criteria": {"Keep FastQC": null, "Drop MultiQC": null, "Keep MultiQC": null}}, "target": "Keep MultiQC", "target_idx": 2}
{"id": "mod_maxbin2_0", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: MaxBin is a software that is capable of clustering metagenomic contigs (tools: maxbin2)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"amps": "Post-processing script of the MaltExtract component of the HOPS package", "fasta_vclust_prefilter_align_cluster": "Subworkflow that runs a three-stage VCLUST pipeline: 1) create a prefilter\nof candidate sequence pairs with `v", "bracken/bracken": "Re-estimate taxonomic abundance of metagenomic samples analyzed by kraken.", "hifiadapterfilt/downloaddb": "Downloads the pre-built PacBio adapter BLAST database from the HiFiAdapterFilt\nGitHub repository. The database", "maxbin2": "MaxBin is a software that is capable of clustering metagenomic contigs"}}, "target": "maxbin2", "target_idx": 4}
{"id": "samplesheet_arch_pacbio_hifi_wgs_6_1", "category": "samplesheet_schema", "state": {"pipeline": "nf-core/genomeassembler", "assay_type": "Long-read Pacific Biosciences HiFi sequencing", "data_format": "Single HiFi BAM or FastQ"}, "question": {"type": "choice", "instructions": "Which columns are standard for 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_annotsv_annotsv_2", "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_low": null, "process_long": null, "process_medium": null}}, "target": "process_single", "target_idx": 0}
{"id": "mod_savana_cna_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: Copy-number aberration calling with SAVANA for long-read tumour/normal alignments. (tools: savana)?", "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.", "cnvnator_convert2vcf": "convert2vcf.pl is command line tool to convert CNVnator calls to vcf format.", "controlfreec_freec": "Copy number and genotype annotation from whole genome and whole exome sequencing data", "savana_cna": "Copy-number aberration calling with SAVANA for long-read tumour/normal alignments.", "mmseqs_fasta_cluster": "Subworkflow that generates a clustering TSV file from a set of amino acid sequence within a FASTA file."}}, "target": "savana_cna", "target_idx": 3}
{"id": "mod_flye_1", "category": "tool_selection", "state": "In Nextflow DSL2, which module handles: De novo assembler for single molecule sequencing reads (tools: flye)?", "question": {"type": "choice", "instructions": "Select the appropriate nf-core module for the specified bioinformatics operation.", "criteria": {"perbase": "Per-base metrics on BAM/CRAM files.", "flye": "De novo assembler for single molecule sequencing reads", "fastavalidator": "\"Python C-extension for a simple validator for fasta files. The module emits the validated file or an\nerror lo", "abricate_summary": "Screen assemblies for antimicrobial resistance against multiple databases", "abricate_run": "Screen assemblies for antimicrobial resistance against multiple databases"}}, "target": "flye", "target_idx": 1}
{"id": "resource_bwa_aln_2", "category": "resource_profiling", "state": {"process": "BWA_ALN", "tool": "bwa/aln", "description": "Find SA coordinates of the input reads for bwa short-read mapping"}, "question": {"type": "choice", "instructions": "What resource profile label should be assigned to BWA_ALN (Find SA coordinates of the input reads for bwa short-read mapping) in conf/base.config?", "criteria": {"process_single": null, "process_medium": null, "process_high": null, "process_low": null}}, "target": "process_high", "target_idx": 2}