bio-atac-seq-atac-peak-calling

SkillFiles & storage

Lets your agent identify open chromatin regions from ATAC-seq data using MACS3 with tuned parameters.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the bio-atac-seq-atac-peak-calling skill

About this capability

Call accessible chromatin regions from ATAC-seq data using MACS3 with ATAC-specific parameters. Use when identifying open chromatin regions from aligned ATAC-seq BAM files, different from ChIP-seq peak calling.

What this skill tells your AI

The instructions your AI receives, as published by freedomintelligence/openclaw-medical-skills in skills/bio-atac-seq-atac-peak-calling/SKILL.md and read by ahel’s review.

Version Compatibility

Reference examples tested with: Bowtie2 2.5.3+, MACS3 3.0+, samtools 1.19+

Before using code patterns, verify installed versions match. If versions differ:

  • CLI: <tool> --version then <tool> --help to confirm flags

If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.

ATAC-seq Peak Calling

"Call peaks from my ATAC-seq data" → Identify open chromatin regions using ATAC-specific parameters (no input control, shifted Tn5 cut sites, paired-end mode).

  • CLI: macs3 callpeak -t atac.bam -f BAMPE -g hs --nomodel --shift -75 --extsize 150

Basic MACS3 for ATAC-seq

Goal: Identify open chromatin regions from ATAC-seq data using ATAC-specific peak calling parameters.

Approach: Run MACS3 in paired-end mode with Tn5 shift correction, no model building, and duplicate retention since ATAC-seq generates natural duplicates at accessible sites.

# Standard ATAC-seq peak calling
macs3 callpeak \
    -t sample.bam \
    -f BAMPE \
    -g hs \
    -n sample \
    --outdir peaks/ \
    -q 0.05 \
    --nomodel \
    --shift -75 \
    --extsize 150 \
    --keep-dup all \
    -B

Key ATAC-seq Parameters

# Explained parameters
macs3 callpeak \
    -t sample.bam \        # Treatment BAM
    -f BAMPE \             # Paired-end BAM (uses fragment size)
    -g hs \                # Genome size: hs (human), mm (mouse)
    -n sample \            # Output name prefix
    --nomodel \            # Don't build shifting model
    --shift -75 \          # Shift reads to center on Tn5 cut site
    --extsize 150 \        # Extend reads to this size
    --keep-dup all \       # Keep duplicates (ATAC has natural duplicates)
    -B \                   # Generate bedGraph for visualization
    --call-summits         # Call peak summits

Why These Parameters?

ParameterReason
--nomodelATAC doesn't have control, can't build model
--shift -75Centers on Tn5 insertion site
--extsize 150Smooths signal around cut sites
--keep-dup allTn5 creates duplicate cuts at accessible sites
-f BAMPEUses actual fragment size from paired-end

Paired-End vs Single-End

# Paired-end (recommended for ATAC)
macs3 callpeak -f BAMPE -t sample.bam ...

# Single-end (less common)
macs3 callpeak -f BAM -t sample.bam \
    --nomodel --shift -75 --extsize 150 ...

Call Peaks on NFR Only

Goal: Call peaks using only nucleosome-free fragments for sharper regulatory element detection.

Approach: Filter BAM to fragments <100 bp (NFR), then call peaks with adjusted shift/extsize parameters matching the shorter fragment size.

# First, filter to nucleosome-free reads (<100bp fragments)
samtools view -h sample.bam | \
    awk 'substr($0,1,1)=="@" || ($9>0 && $9<100) || ($9<0 && $9>-100)' | \
    samtools view -b > nfr.bam

# Call peaks on NFR
macs3 callpeak \
    -t nfr.bam \
    -f BAMPE \
    -g hs \
    -n sample_nfr \
    --nomodel \
    --shift -37 \
    --extsize 75 \
    --keep-dup all \
    -q 0.01

Broad Peaks (Optional)

# For broader accessible regions
macs3 callpeak \
    -t sample.bam \
    -f BAMPE \
    -g hs \
    -n sample_broad \
    --nomodel \
    --shift -75 \
    --extsize 150 \
    --broad \
    --broad-cutoff 0.1

Batch Processing

Goal: Call peaks on multiple ATAC-seq samples in one pass.

Approach: Loop over BAM files and run MACS3 with consistent ATAC-specific parameters for each sample.

#!/bin/bash
GENOME=hs  # hs for human, mm for mouse
OUTDIR=peaks

mkdir -p $OUTDIR

for bam in *.bam; do
    sample=$(basename $bam .bam)
    echo "Processing $sample..."

    macs3 callpeak \
        -t $bam \
        -f BAMPE \
        -g $GENOME \
        -n $sample \
        --outdir $OUTDIR \
        --nomodel \
        --shift -75 \
        --extsize 150 \
        --keep-dup all \
        -q 0.05 \
        -B \
        --call-summits
done

Output Files

FileDescription
_peaks.narrowPeakPeak locations (BED-like)
_summits.bedPeak summit positions
_peaks.xlsPeak statistics (Excel format)
_treat_pileup.bdgSignal track (bedGraph)
_control_lambda.bdgBackground (if control provided)

narrowPeak Format

chr1  100  500  peak1  500  .  10.5  50.2  45.1  200

Columns: chrom, start, end, name, score, strand, signalValue, pValue, qValue, summit_offset

Convert to BigWig

# Sort bedGraph
sort -k1,1 -k2,2n sample_treat_pileup.bdg > sample.sorted.bdg

# Convert to BigWig
bedGraphToBigWig sample.sorted.bdg chrom.sizes sample.bw

Merge Replicates

# Pool BAMs before peak calling (recommended for final peaks)
samtools merge -@ 8 merged.bam rep1.bam rep2.bam rep3.bam

# Call peaks on merged
macs3 callpeak -t merged.bam -f BAMPE -g hs -n merged ...

IDR for Replicate Consistency

Goal: Identify reproducible peaks across biological replicates using the Irreproducible Discovery Rate framework.

Approach: Call peaks on each replicate independently, then run IDR to score peak reproducibility and filter to a high-confidence set.

# Call peaks on each replicate
macs3 callpeak -t rep1.bam -f BAMPE -g hs -n rep1 ...
macs3 callpeak -t rep2.bam -f BAMPE -g hs -n rep2 ...

# Run IDR
idr --samples rep1_peaks.narrowPeak rep2_peaks.narrowPeak \
    --input-file-type narrowPeak \
    --output-file idr_peaks.txt \
    --plot

# Filter by IDR threshold
awk '$5 >= 540' idr_peaks.txt > reproducible_peaks.bed

Related Skills

  • read-alignment/bowtie2-alignment - Align ATAC-seq reads
  • atac-seq/atac-qc - Quality control
  • chip-seq/peak-calling - ChIP-seq comparison
  • genome-intervals/bed-file-basics - Work with peak files

Signals

GitHub stars
3k
Forks
407
Last commit
Jul 2026
Advanced
Catalog kind
skill
Gateway key
bio-atac-seq-atac-peak-calling-freedomintelligence
Source
github.com/freedomintelligence/openclaw-medical-skills