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ngs-epigenomics-peaks

Dispatch ATAC-seq, ChIP-seq, CUT&RUN, or CUT&Tag requests to assay-specific QC, alignment, signal-track, peak-calling, consensus, and differential peak workflows.

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Epigenomics Peaks

Use this skill as the epigenomics dispatcher for ATAC-seq, ChIP-seq, CUT&RUN, or CUT&Tag analysis. Hand off to the assay-specific deep skill once the assay type is known.

Essential Inputs

Confirm:

  • assay type
  • FASTQ or BAM input
  • organism and genome build
  • blacklist file, if available
  • control samples: input DNA, IgG, or spike-in
  • biological replicates
  • peak type: narrow, broad, accessibility, or protocol-specific
  • desired outputs: QC report, peaks, consensus peaks, bigWigs, differential peaks

Public Defaults

Choose the workflow by assay:

  • ATAC-seq: ngs-atacseq-peaks-qc using nf-core/atacseq by default
  • ChIP-seq: ngs-chip-cutrun-peaks-qc using nf-core/chipseq by default
  • CUT&RUN or CUT&Tag: ngs-chip-cutrun-peaks-qc using nf-core/cutandrun by default

Use direct MACS2 only for focused peak-calling tasks from prepared BAMs.

Preflight

python plugins/ngs-analysis/scripts/ngs_preflight.py --pipeline epigenomics_peaks --emit-install-plan

Local Execution Package

For FASTQ intake/QC over ATAC-seq, ChIP-seq, CUT&RUN, or CUT&Tag data, use the shared FASTQ assay package:

python plugins/ngs-analysis/scripts/run_fastq_assay_package.py \
  --lane epigenomics_peaks \
  --sample-sheet assay_samples.csv \
  --execute

This validates sample-sheet paths and read structure, runs seqkit stats and FastQC/MultiQC when available, and writes peak_calling_readiness.json. Full alignment, signal tracks, TSS/FRiP, consensus peaks, and differential analyses still route through the assay-specific workflow.

Assay-specific ATAC and ChIP/CUT&RUN runners now also emit native review files alongside TSV/JSON summaries: qc/*_dashboard.html, FRiP/peak SVG plots, insert-size SVG plots, browser-track preview HTML, UCSC track lines, and IGV session files.

Kickoff Pattern

ATAC-seq preflight run:

nextflow run nf-core/atacseq \
  -profile test,docker \
  --outdir results/atacseq_test

ChIP-seq preflight run:

nextflow run nf-core/chipseq \
  -profile test,docker \
  --outdir results/chipseq_test

CUT&RUN/CUT&Tag preflight run:

nextflow run nf-core/cutandrun \
  -profile test,docker \
  --outdir results/cutandrun_test

Carry replicate and control metadata through the sample sheet before running real analysis.

Repository
openai/plugins
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