データ・AIのスキル

Orchestrates the untargeted LC-MS metabolomics pipeline end-to-end (xcms 4.x feature extraction, QC/drift/normalization, confidence-stratified annotation, permutation-validated statistics, background-aware pathway mapping), naming what each stage decides and where it silently fails. Use when running a full LC-MS metabolomics study from raw mzML to enriched pathways and needing the honest handoffs between stages. Each stage defers to its component skill for parameters and traps; for stable-isotope flux (a separate branch, not this untargeted flow) see metabolomics/isotope-tracing.

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Authors portable, strongly-typed bioinformatics pipelines in the Common Workflow Language (CWL v1.2) as CommandLineTool/Workflow/ExpressionTool documents, validated with cwltool and run at scale on Toil/Arvados/Calrissian. Use when deciding CWL (portability/provenance/regulated) vs Nextflow/WDL/Snakemake; declaring secondaryFiles for indexed companions (.bai/.fai/.dict/.tbi and the caret rule); putting resources/containers under requirements (must-hold) vs hints (advisory) to avoid silent OOM; choosing scatterMethod (dotproduct vs flat_/nested_crossproduct); preferring $(...) parameter refs over ${...} JavaScript for portability; pinning DockerRequirement images; or emitting a CWLProv provenance object for audited/clinical settings.

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Orchestrates an end-to-end long-read structural-variant pipeline - basecalling to minimap2 alignment (platform-matched preset) to Sniffles2/cuteSV/pbsv calling to optional assembly-based calling (dipcall/PAV) to two-step .snf cohort merging to Truvari benchmarking - chaining ONT and PacBio HiFi runs while handing the SV signal mechanism off to the component skills. Use when running a long-read SV workflow from reads to a benchmarked callset, choosing the minimap2 preset and SV caller by platform and goal, deciding when long reads are worth it for the insertions and repeat-mediated SVs short reads physically miss, building a joint-genotyped cohort with the two-step .snf design, or parameterizing a Truvari benchmark against GIAB HG002 Tier 1 plus CMRG. Not for the SV signal mechanism itself (see variant-calling/structural-variant-calling) or short-read SV.

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End-to-end CLIP-seq pipeline from FASTQ to ENCODE-compliant binding sites, single-nucleotide crosslink maps, annotation, motifs, and (optionally) differential binding. Use when running the full Yeo lab eCLIP / iCLIP / iCLIP2 / iCLIP3 / irCLIP / PAR-CLIP analysis with SMInput control, protocol-specific UMI extraction, ENCODE STAR parameters, CLIPper or Skipper peak calling with stringent log2 FC and -log10 p thresholds, IDR rescue and self-consistency QC, and downstream motif registration with mCross or PEKA.

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Authors reproducible bioinformatics pipelines with Snakemake - rules wired by output-file pattern, wildcards and expand() for sample fan-out, checkpoints for runtime-unknown outputs, resource/retry escalation, and conda/container software deployment on HPC and cloud. Use when deciding rule-based (Snakemake) vs channel/dataflow (Nextflow) authoring; wiring rules by OUTPUT-file pattern rather than imperative order; using wildcards + expand() for sample fan-out and constraining them to stop silent mis-routing; adding checkpoints when the set of outputs is unknown until a step runs (dynamic DAG); diagnosing why a job reran (or did not) under the mtime-plus-provenance trigger set; escalating memory on retry for OOM-killed jobs; and porting a Snakemake 7 `--cluster`/remote-provider command to the Snakemake 8+ executor-plugin and storage-plugin model (snakemake-executor-plugin-slurm) with `--software-deployment-method`.

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End-to-end pooled and single-cell CRISPR screen analysis from FASTQ to hit genes. Orchestrates library design QC, guide counting, six-stage screen QC (plasmid Gini, replicate Pearson, CEGv2 PR-AUC, copy-number artifact), method-appropriate hit calling across MAGeCK RRA/MLE, BAGEL2, drugZ, JACKS, and Chronos, cancer-cell-line copy-number correction (CRISPRcleanR / Chronos), batch correction for multi-batch screens, and the specialized branches for combinatorial paralog screens, single-cell Perturb-seq, base-editor variant-function screens, prime-editor screens, and in vivo bottleneck-aware screens. Use when analyzing any pooled CRISPR screen end-to-end, matching the hit-calling method to the experimental design, integrating copy-number correction into the pipeline, or branching the workflow for single-cell, combinatorial, base-editor, prime-editor, or in vivo variants.

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End-to-end alternative splicing analysis from FASTQ to differential splicing results for short-read bulk RNA-seq. Aligns with STAR 2-pass cohort-style, performs junction QC (RSeQC, MaxEntScan, SpliceAI), runs rMATS-turbo and leafcutter for concordant differential analysis, optionally MAJIQ V3 for complex events / heterogeneous cohorts, isoform-switching with NMD/ORF/domain consequences (IsoformSwitchAnalyzeR v2 + DRIMSeq+DEXSeq+stageR DTU), and sashimi visualizations. Use when performing comprehensive splicing analysis from raw bulk RNA-seq data; for variant-driven splice prediction see splice-variant-prediction; for rare-disease single-patient outlier detection see outlier-splicing-detection; for full-isoform PacBio/ONT analysis see long-read-splicing.

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End-to-end GWAS workflow from VCF to association results. Covers PLINK QC, population structure correction, and association testing for case-control or quantitative traits. Use when running genome-wide association studies.

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Orchestrates an end-to-end CRISPR editing experiment design from target gene to delivery-ready, validatable constructs. Sequences guide design, off-target assessment, edit-modality selection (knockout, base editing, prime editing, HDR knock-in), and template/donor design, with a QC checkpoint at each handoff. Use when designing a complete CRISPR experiment for knockout, point correction, or tagging and the order of operations, the modality decision, and the cross-cutting traps are needed rather than a single step. Defers each step's mechanics to the genome-engineering skills.

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End-to-end flow, spectral, and mass cytometry (CyTOF) pipeline from raw FCS files to differentially abundant/expressed cell populations. Orchestrates the read -> compensate/unmix -> transform -> QC -> doublet-removal -> cluster-or-gate -> annotate -> diffcyt DA/DS chain with flowCore/CATALYST/diffcyt, branching on instrument type and on clustering-vs-gating. Use when processing a cytometry experiment end-to-end, deciding the pipeline path for an instrument, or wiring the flow-cytometry component skills into one analysis with valid sample-level statistics.

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End-to-end clinical trial analysis workflow from CDISC SDTM/ADaM loading through ICH E9(R1) estimand-driven primary analysis to CONSORT 2025 regulatory-compliant reporting. Covers data preparation, FDA 2023 marginal vs conditional logistic regression, categorical tests with Boschloo, modern HTE/subgroup methods, missing-data sensitivity (MMRM, reference-based MI, Permutt tipping point), graphical multiplicity (Bretz-Maurer), survival analysis (Cox/RMST/competing risks) when applicable, and Table 1. Use when performing a complete analysis of clinical trial data.

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Orchestrates the end-to-end germline short-variant pipeline from FASTQ to a filtered, normalized, benchmarked VCF, chaining QC/trim, BWA-MEM2 alignment, duplicate marking, optional BQSR, calling (bcftools/GATK HaplotypeCaller/DeepVariant/DRAGEN), normalization, site+genotype filtering, annotation, and hap.py/vcfeval benchmarking. Use when deciding the pipeline-wide reference-genome commitment (GRCh38 analysis set vs T2T, ALT/decoy handling), sequencing the steps in the defensible order (normalize BEFORE annotate, filter site- then genotype-level), choosing the calling engine and single-sample vs cohort joint-calling, picking a filtering strategy by cohort size, or benchmarking stratified within GIAB confident regions. Hands off mechanism to the variant-calling and read-alignment component skills; not a re-teach of any single step.

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End-to-end multi-omics integration workflow. Orchestrates data harmonization, MOFA/mixOmics integration, factor interpretation, and downstream analysis across transcriptomics, proteomics, metabolomics, and other modalities. Use when integrating multiple omics datasets.

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End-to-end shotgun metagenomics workflow from FASTQ to taxonomic and functional profiles, orchestrating controls/host depletion, Kraken2+Bracken classification, MetaPhlAn marker profiling, and HUMAnN functional profiling. Covers the controls-first ordering, why Kraken2 read counts are not abundances and MetaPhlAn cell fractions do not equal Bracken read fractions, and the consistent-pipeline framing. Use when profiling shotgun metagenomic samples end to end, or chaining classification, abundance, and function. For resistome see metagenomics/amr-detection; for strains see metagenomics/strain-tracking; for assembly see genome-assembly/metagenome-assembly.

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Orchestrates an end-to-end MeRIP-seq / m6A-seq analysis from raw FASTQ to differential m6A peak calls and metagene plots, chaining fastp adapter trimming, STAR splice-aware alignment (NO deduplication for non-UMI MeRIP), deepTools replicate-concordance + IP-enrichment QC, PreSeq saturation curves, exomePeak2 (transcript-aware Poisson GLM) peak calling, optional MACS3 broad-peak cross-check, DRACH motif confirmation as a sanity check (NOT a per-peak filter), exomePeak2 differential calling via the four-BAM-vector interface (bam_ip + bam_input control; bam_treated_ip + bam_treated_input treatment), ChIPseeker annotation, and the canonical Guitar metagene with stop-codon enrichment as the biological QC anchor. Use when running a complete MeRIP analysis from raw reads, when chaining the constituent epitranscriptomics skills (merip-preprocessing -> m6a-peak-calling -> m6a-differential -> modification-visualization), or when wrapping the pipeline in Snakemake / Nextflow.

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Authors bioinformatics pipelines in WDL (Workflow Description Language) run by Cromwell or miniwdl, targeting the GATK/Broad and Terra/AnVIL/BioData Catalyst cloud ecosystem, with tasks, workflows, scatter-gather parallelism, structs, and a runtime block that sizes the cloud VM. Use when deciding to target Terra/AnVIL/GATK/WARP (chosen for the ecosystem, not the language); sizing runtime disks dynamically for a fresh-per-task cloud VM (ceil(size(f)*factor)+buffer); choosing preemptible vs on-demand VMs by task length and idempotency; picking Cromwell (production, cloud, call-caching) vs miniwdl (local dev, miniwdl check linting, readable errors); enabling and debugging call-caching silent-miss modes; pinning Docker by digest for reproducibility and cache stability; or scattering an array for parallel fan-out.

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End-to-end Hi-C analysis workflow from FASTQ to compartments, TADs, and loops, with the decision of WHICH features the sequencing depth can support. Covers pairtools read-pair processing and library QC, cooler matrices, ICE balancing and distance-decay expected, A/B compartments, TAD boundaries, loop calling, and the routing of HiChIP/PLAC-seq/Capture Hi-C to protein-directed loop callers. Use when processing Hi-C data end to end, deciding a resolution for a given depth, or choosing between bulk-Hi-C and protein-directed loop calling.

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End-to-end bisulfite sequencing workflow from FASTQ to differentially methylated regions. Covers Bismark alignment, methylation calling, and DMR detection with methylKit. Use when analyzing bisulfite sequencing data.

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End-to-end eDNA metabarcoding from raw amplicons to community ecology. Covers QC, primer removal (mandatory before DADA2 filterAndTrim), denoising with OBITools3 v3 (obi stats plural; DMS-based) or DADA2 ASVs (Callahan 2017), decontam combined method as screening-not-classifier (Davis 2018), tag-jumping with NovaSeq 10x MiSeq caveat (Schnell 2015), Hill-number effective species counts with coverage-based rarefaction (Jost 2006; Chao & Jost 2012; doubling rule), beta-diversity decomposition with MANDATORY PERMANOVA + PERMDISP pair (Anderson & Walsh 2013), constrained ordination, and the read-counts-not-abundance critique (Lamb 2019). Use when processing eDNA samples for biodiversity assessment, deciding ASV vs OTU, configuring OBITools3 v3, interpreting decontam screening, or reporting community comparisons with the dispersion confound check.

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End-to-end ChIP-seq workflow from FASTQ files to annotated peaks. Covers QC, alignment, peak calling with MACS3 (or HOMER), and peak annotation with ChIPseeker. Use when processing ChIP-seq data from alignment through peak annotation.

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End-to-end 16S/ITS amplicon workflow from demultiplexed FASTQ to a consensus differential-abundance result, orchestrating cutadapt primer removal, per-run DADA2 ASV inference (learnErrors/mergeSequenceTables/removeBimeraDenovo), region-matched taxonomy assignment, a SEPP/Greengenes2 tree, alpha/beta diversity at a declared sampling depth (phyloseq/vegan, adonis2 paired with betadisper), compositional DA as a consensus of >=2 tools (ALDEx2/ANCOM-BC2) on unrarefied counts, and optional PICRUSt2 functional prediction gated on NSTI. Covers the stage-ordering decisions (primers before truncation, per-run error model, rarefy for diversity not DA, predicted potential not activity) and defers each per-step choice to the six microbiome skills. Use when staging an amplicon study end to end or chaining ASV inference, taxonomy, diversity, and differential abundance. For shotgun reads see workflows/metagenomics-pipeline.

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End-to-end multiome workflow for joint scRNA-seq + scATAC-seq analysis. Covers data loading, separate modality processing, and WNN integration with Seurat/Signac. Use when analyzing joint scRNA+scATAC data.

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End-to-end biomarker discovery workflow from expression data to validated biomarker panels. Covers feature selection with Boruta/LASSO, leakage-safe cross-validation, calibration, and SHAP interpretation. Use when building and validating diagnostic or prognostic biomarker signatures from omics data.

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End-to-end ATAC-seq workflow from FASTQ files to differential accessibility and TF footprinting. Covers alignment, peak calling with MACS3, QC metrics, and optional TOBIAS footprinting. Use when running end-to-end ATAC-seq analysis from FASTQ to differential accessibility.

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