ngs-epigenomics-peaks — Codex skill: ATAC-seq, ChIP-seq, CUT&RUN
Routes ATAC-seq, ChIP-seq, CUT&RUN and CUT&Tag work to the right pipeline: QC, alignment, signal tracks, peak calling, consensus and differential peaks.
npx skills add openai/plugins --skill ngs-epigenomics-peaks -a codexWhat ngs-epigenomics-peaks does
This skill acts as a dispatcher. It first pins down the assay, the input files, organism and genome build, control samples, replicates and the peak type you want. Once the assay is clear, the request goes to a deep skill for that protocol: ATAC-seq to ngs-atacseq-peaks-qc with nf-core/atacseq, ChIP-seq to ngs-chip-cutrun-peaks-qc with nf-core/chipseq, and CUT&RUN or CUT&Tag to the same skill with nf-core/cutandrun. Direct MACS2 stays for narrow peak-calling jobs on BAMs you already have.
An environment check runs first: python plugins/ngs-analysis/scripts/ngs_preflight.py --pipeline epigenomics_peaks --emit-install-plan. For FASTQ intake and QC there is a shared package: python plugins/ngs-analysis/scripts/run_fastq_assay_package.py --lane epigenomics_peaks --sample-sheet assay_samples.csv --execute. It checks sample-sheet paths and read structure, runs seqkit stats and FastQC/MultiQC when present, and writes peak_calling_readiness.json. Alignment, signal tracks, TSS/FRiP, consensus and differential peaks still go through the assay-specific workflow.
The ATAC and ChIP/CUT&RUN runners also drop review files next to the TSV/JSON summaries: qc/*_dashboard.html, SVG plots for FRiP and peaks, insert-size SVGs, a browser-track preview HTML, UCSC track lines and IGV session files. Replicate and control metadata has to be carried through the sample sheet before you run the real analysis, or the pipeline will not line up the comparisons.
What it helps with
- pick the right pipeline for a given epigenomics assay
- validate sample-sheet paths and read structure before a run
- produce a FASTQ QC report ahead of alignment
- get consensus and differential peaks
- open signal tracks in IGV or UCSC
Example prompts for the agent
- Run the epigenomics preflight:
python plugins/ngs-analysis/scripts/ngs_preflight.py --pipeline epigenomics_peaks --emit-install-plan - I have ATAC-seq FASTQ, human, hg38, two replicates — what do I need for peak calling?
- Run FASTQ QC with
python plugins/ngs-analysis/scripts/run_fastq_assay_package.py --lane epigenomics_peaks --sample-sheet assay_samples.csv --execute
How to install ngs-epigenomics-peaks
1Skills CLI (Vercel)
npx skills add openai/plugins --skill ngs-epigenomics-peaks -a codex2Manually: put the files in place
.agents/skills/ngs-epigenomics-peaks/SKILL.mdFor all projects use ~/.agents/skills/
1Skills CLI (Vercel)
npx skills add openai/plugins --skill ngs-epigenomics-peaks -a claude-code2Manually: put the files in place
~/.claude/skills/ngs-epigenomics-peaks/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/ngs-epigenomics-peaks/
Manually: put the files in place
.cursor/skills/ngs-epigenomics-peaks/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install openai/plugins ngs-epigenomics-peaks2Manually: put the files in place
.github/skills/ngs-epigenomics-peaks/SKILL.mdPlatform CLI
gemini skills install https://github.com/openai/plugins --path plugins/ngs-analysis/skills/ngs-epigenomics-peaksManually: put the files in place
.devin/skills/ngs-epigenomics-peaks/SKILL.mdThe legacy .windsurf/skills/ path still works
Claude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
Step by step, with commands for each platform: Codex skills: how to install, where they live, how to call them
Questions about ngs-epigenomics-peaks
How do I install ngs-epigenomics-peaks in Claude?
Run npx skills add openai/plugins --skill ngs-epigenomics-peaks, then npx skills add openai/plugins --skill ngs-epigenomics-peaks -a codex. The skill then sits at .agents/skills/ngs-epigenomics-peaks/SKILL.md.
What does ngs-epigenomics-peaks do?
It dispatches ATAC-seq, ChIP-seq, CUT&RUN and CUT&Tag requests. It collects the analysis parameters and hands off to the skill for that protocol, covering QC, alignment, signal tracks, peak calling, consensus and differential analysis.
Which pipelines does it use by default?
nf-core/atacseq for ATAC-seq, nf-core/chipseq for ChIP-seq, and nf-core/cutandrun for CUT&RUN or CUT&Tag. Direct MACS2 is only for peak calling on prepared BAMs.
Source text
SKILL.md · MIT
--- name: ngs-epigenomics-peaks description: 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. --- # 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.
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