ngs-epigenomics-peaks

# 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 ```bash 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: ```bash 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: ```bash nextflow run nf-core/atacseq \ -profile test,docker \ --outdir results/atacseq_test ``` ChIP-seq preflight run: ```bash nextflow run nf-core/chipseq \ -profile test,docker \ --outdir results/chipseq_test ``` CUT&RUN/CUT&Tag preflight run: ```bash 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.