atac-seq

name	atac-seq
description	ATAC-seq processing with assay QC, MACS3 peak calling, consensus peak matrices, differential accessibility, and motif or footprint follow-up.
tool_type	mixed
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 \
  -q 0.01 \
  --outdir results/peaks

BAMPE piles up the real fragments inferred from the read pairs. MACS3 zeroes --shift whenever the format is BAMPE/BEDPE/FRAG, and takes the fragment length from the pairs rather than --extsize, so passing --nomodel --shift -100 --extsize 200 alongside -f BAMPE changes nothing. To pile up Tn5 insertion sites instead, drop to single-end mode where those flags apply:

macs3 callpeak -t atac.bam -f BAM -g hs -n sample -q 0.01 --nomodel --shift -100 --extsize 200

Key Parameters

Parameter	Typical value	Notes
-f	BAMPE	paired-end fragment mode; BAM for the insertion-site workflow
--nomodel	-f BAM only	pairs with --shift/--extsize; ignored under BAMPE
--shift	-100	Tn5 offset; MACS3 forces it to 0 under BAMPE
--extsize	200	smoothing window for the shifted cut sites; BAMPE uses real fragment length
-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 (-f BAMPE), or single-end mode with Tn5-aware shifting (-f BAM --nomodel --shift -100 --extsize 200). The two are alternatives — BAMPE discards the shift.

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

Quality Review

• TSS enrichment below 7 should trigger caution.
• Strong nucleosome periodicity supports a good bulk ATAC library.
• FRiP below 0.1 is usually weak and needs scrutiny.
• Footprinting should not be trusted on low-depth or poor-quality libraries.

Anti-Patterns

• using generic ChIP peak-calling defaults for ATAC
• running footprinting on weak libraries
• skipping TSS enrichment review
• merging peaks from mixed reference builds

Related Skills

• ChIP Seq
• Gene Regulatory Networks
• Multiome And scATAC

Optional Supplements

• deeptools
• pysam