Agent Skills › Runchuan-BU/BioClaw › atac-seq

atac-seq

GitHub

用于批量ATAC-seq数据分析，涵盖QC质控、MACS3峰调用、共识矩阵构建、差异可及性分析及motif/footprint后续分析。

container/skills/atac-seq/SKILL.md Runchuan-BU/BioClaw

Trigger Scenarios

需要进行ATAC-seq数据质控执行peak calling或差异可及性分析

Install

npx skills add Runchuan-BU/BioClaw --skill atac-seq -g -y

More Options

Non-standard path

npx skills add https://github.com/Runchuan-BU/BioClaw/tree/main/container/skills/atac-seq -g -y

Use without installing

npx skills use Runchuan-BU/BioClaw@atac-seq

指定 Agent (Claude Code)

npx skills add Runchuan-BU/BioClaw --skill atac-seq -a claude-code -g -y

安装 repo 全部 skill

npx skills add Runchuan-BU/BioClaw --all -g -y

预览 repo 内 skill

npx skills add Runchuan-BU/BioClaw --list

SKILL.md

Frontmatter

{
    "name": "atac-seq",
    "tool_type": "mixed",
    "description": "ATAC-seq processing with assay QC, MACS3 peak calling, consensus peak matrices, differential accessibility, and motif or footprint follow-up.",
    "primary_tool": "MACS3"
}

ATAC Seq

Version Compatibility

Reference examples assume:

macs3 3.0+
samtools 1.18+
deepTools 3.5+

Verify the runtime first:

CLI: macs3 --version, samtools --version, bamCoverage --version

Overview

Use this skill when the user needs:

bulk ATAC-seq QC
peak calling
accessibility counting
differential accessibility
motif deviation or footprint follow-up

When To Use This Skill

the task is bulk ATAC-seq rather than ChIP-seq
TSS enrichment, fragment periodicity, or FRiP need review
the output should include peaks, counts, and downstream accessibility summaries

Quick Route

paired-end bulk ATAC: use BAMPE
call peaks without control using ATAC-specific settings
if TSS enrichment is poor, stop and flag data quality before interpretation

Progressive Disclosure

Read technical_reference.md for QC gates and assay-specific caveats.
Read commands_and_thresholds.md for peak-calling commands, thresholds, and output conventions.

Prerequisites

Check	Guidance
uniquely mapped reads	`>= 20M` preferred for strong bulk ATAC
TSS enrichment	`> 7` acceptable, `> 10` strong
FRiP	`> 0.2` often strong for good bulk ATAC

Expected Inputs

paired-end ATAC BAM or FASTQ
reference genome
sample groups for comparisons

Expected Outputs

results/peaks/sample_peaks.narrowPeak
results/matrix/consensus_peak_counts.tsv
results/diff_accessibility.tsv
figures/tss_enrichment.pdf
figures/fragment_size_distribution.pdf

Starter Pattern

macs3 callpeak \
  -t atac.bam \
  -f BAMPE \
  -g hs \
  -n sample \
  --nomodel \
  --shift -100 \
  --extsize 200 \
  -q 0.01 \
  --outdir results/peaks

Key Parameters

Parameter	Typical value	Notes
`-f`	`BAMPE`	paired-end ATAC should use fragment-aware mode
`--nomodel`	on	standard for ATAC
`--shift`	`-100`	common Tn5 offset convention
`--extsize`	`200`	common first-pass extension
`-q`	`0.01`	starting FDR threshold

Workflow

1. Validate assay QC

Review:

TSS enrichment
fragment size periodicity
duplication
mapped read depth

2. Call peaks with ATAC-specific settings

Use fragment-aware paired-end mode and Tn5-aware shifting or equivalent settings.

3. Build a consensus peak matrix

Merge peaks across samples, count fragments into consensus intervals, then produce a peak-by-sample matrix.

4. Test differential accessibility

Use replicate-aware statistics and report both effect size and adjusted significance.

5. Run motif or footprint follow-up

Only after peak quality and read depth support it.

Output Artifacts

results/
├── peaks/
│   ├── sample_peaks.narrowPeak
│   └── sample_summits.bed
├── matrix/
│   └── consensus_peak_counts.tsv
└── diff_accessibility.tsv
qc/
├── tss_enrichment.tsv
└── fragment_metrics.tsv
figures/
├── tss_enrichment.pdf
└── fragment_size_distribution.pdf