# ngs-atacseq-peaks-qc

Plans and runs ATAC-seq QC, alignment, and peak-calling workflows. It checks library quality metrics, nucleosome periodicity, and chromatin accessibility.

- skill · `type=skill` · Codex, ChatGPT · 2 installs · ★ 7604
- Author: OpenAI · official OpenAI repository
- License: MIT · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/openai/plugins/tree/HEAD/plugins/ngs-analysis/skills/ngs-atacseq-peaks-qc/SKILL.md
- Updated: 2026-10-08
- HTML: https://affpapa.org/en/nevibecode/skills/ngs-atacseq-peaks-qc

## What it does

The skill coordinates ATAC-seq analysis pipelines starting from raw FASTQ reads or aligned BAM files. It inspects experimental parameters beforehand: paired-end status, mitochondrial contig names, reference blacklists, and Tn5 transposase shifting. For full reproducible runs, the skill defaults to `nf-core/atacseq`. Direct MACS2 calls remain reserved for pre-aligned BAM files where duplicate filtering is already resolved.

Local processing executes through the `run_atacseq_peaks_qc.py` helper alongside a Bowtie 2 index. The workflow outputs TSV summary metrics, an interactive `qc/atacseq_qc_dashboard.html` report, SVG insert-size plots, and bigWig browser tracks. Providing `--run-motifs` initiates HOMER motif enrichment directly during the run.

Weak replicate concordance or inadequate metadata halts the workflow before differential accessibility testing starts. For antibody-targeted experiments such as ChIP-seq or CUT&Tag, use the dedicated `ngs-chip-cutrun-peaks-qc` skill instead.

## Install

### Codex (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add openai/plugins --skill ngs-atacseq-peaks-qc -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/ngs-atacseq-peaks-qc/SKILL.md` — For all projects use ~/.agents/skills/

### Claude Code

1. **Skills CLI (Vercel)**
```bash
npx skills add openai/plugins --skill ngs-atacseq-peaks-qc -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/ngs-atacseq-peaks-qc/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/ngs-atacseq-peaks-qc/

### Cursor

**Manually: put the files in place**
- File: `.cursor/skills/ngs-atacseq-peaks-qc/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install openai/plugins ngs-atacseq-peaks-qc
```

2. **Manually: put the files in place**
- File: `.github/skills/ngs-atacseq-peaks-qc/SKILL.md`

### Gemini CLI

**Platform CLI**
```bash
gemini skills install https://github.com/openai/plugins --path plugins/ngs-analysis/skills/ngs-atacseq-peaks-qc
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/ngs-atacseq-peaks-qc/SKILL.md` — The legacy .windsurf/skills/ path still works

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/openai/plugins/tree/HEAD/plugins/ngs-analysis/skills/ngs-atacseq-peaks-qc/SKILL.md

## When to use it
- calculate TSS enrichment and nucleosomal insert-size periodicity
- call accessibility peaks using MACS2 or the nf-core/atacseq pipeline
- generate consensus peak sets and bigWig browser tracks
- screen mitochondrial read fractions and replicate FRiP scores

## Example prompts
- Plan an `nf-core/atacseq` pipeline run for the samples listed in `atac_samples.csv`.
- Run `run_atacseq_peaks_qc.py` using my Bowtie 2 index and TSS BED file to check FRiP.
- Inspect mitochondrial contamination and nucleosomal periodicity in the new ATAC-seq BAM files.

## Source text · SKILL.md · MIT

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````text
---
name: ngs-atacseq-peaks-qc
description: Run or plan ATAC-seq QC, alignment, TSS enrichment, fragment-size, blacklist, peak-calling, consensus peak, and differential accessibility workflows.
---

# ATAC-seq Peaks QC

Use this skill for ATAC-seq accessibility analysis from FASTQ or BAM. If the assay is ChIP-seq, CUT&RUN, CUT&Tag, or antibody-targeted enrichment, use `ngs-chip-cutrun-peaks-qc`.

## Essential Inputs

Confirm:

- FASTQ/BAM inputs and paired-end status
- organism, genome build, blacklist, and mitochondrial contig names
- biological replicates, conditions, batches, and sample metadata
- whether the target is QC only, peaks, consensus peaks, bigWigs, or differential accessibility
- whether Tn5 shifting is handled by the chosen workflow
- desired peak caller and downstream matrix generation

## Route

Prefer `nf-core/atacseq` for full reproducible processing. Use direct MACS2 only when BAMs are already aligned, duplicate/blacklist handling is known, and the user wants focused peak calling.

Preflight command:

```bash
python plugins/ngs-analysis/scripts/ngs_preflight.py --pipeline atacseq_peaks_qc --emit-install-plan
```

For compact read-level intake/QC, use the shared epigenomics execution package:

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

For local-light ATAC alignment, peaks, FRiP, TSS, bigWig tracks, and consensus peaks from FASTQ or prepared BAMs, use the dedicated ATAC runner:

```bash
python plugins/ngs-analysis/scripts/run_atacseq_peaks_qc.py \
  --sample-sheet atac_samples.csv \
  --bowtie2-index /refs/GRCh38/bowtie2/genome \
  --genome-size hs \
  --blacklist-bed /refs/GRCh38/blacklists/encode_blacklist.bed \
  --tss-bed /refs/GRCh38/tss.bed \
  --execute
```

This runner emits `qc/atacseq_qc_summary.{tsv,json}`, `qc/atacseq_qc_dashboard.html`, native SVG FRiP/peak and insert-size plots, browser-track handoff files under `tracks/`, and TSS profile/heatmap commands when `--tss-bed` is supplied. Add `--run-motifs --motif-genome <genome>` when HOMER motif enrichment should be part of the backend run.

It also emits `resources/resource_plan.json`, `resource_manifest.tsv`, `resource_env.sh`, and `resource_readiness.md`. The resource check is advisory by default for local-light runs; add `--genome-build`, `--bundle-root <bundle>=<path>`, and `--require-resource-plan` when missing registered reference bundles should block readiness.

For nf-core execution, use `plugins/ngs-analysis/scripts/run_nfcore_pipeline.py --pipeline atacseq`.

## QC Gates

Review before biological interpretation:

- read depth, alignment rate, duplicate rate, and mitochondrial fraction
- insert-size periodicity/nucleosome pattern
- TSS enrichment and FRiP score when available
- blacklist overlap and peak count per sample
- replicate concordance and consensus peak support
````
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