/bio-atac-seq-atac-peak-calling
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.
$ npx -y skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-atac-seq-atac-peak-calling --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/bio-atac-seq-atac-peak-calling
Context preview
The summary Claude sees to decide when to auto-load this skill.
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.
SKILL.md
bio-atac-seq-atac-peak-calling.SKILL.mdname: bio-atac-seq-atac-peak-calling
description: 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.
tool_type: cli
primary_tool: macs3
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 \
-BKey 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 summitsWhy These Parameters?
| Parameter | Reason | |-----------|--------| | --nomodel | ATAC doesn't have control, can't build model | | --shift -75 | Centers on Tn5 insertion site | | --extsize 150 | Smooths signal around cut sites | | --keep-dup all | Tn5 creates duplicate cuts at accessible sites | | -f BAMPE | Uses 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 0.01Broad 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 0.1Batch 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
doneOutput Files
| File | Description | |------|-------------| | _peaks.narrowPeak | Peak locations (BED-like) | | _summits.bed | Peak summit positions | | _peaks.xls | Peak statistics (Excel format) | | _treat_pileup.bdg | Signal track (bedGraph) | | _control_lambda.bdg | Background (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.bedRelated Skills
- read-al
Read more
name: bio-atac-seq-atac-peak-calling description: 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. tool_type: cli primary_tool: macs3
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 \
-BKey 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 summitsWhy These Parameters?
| Parameter | Reason | |-----------|--------| | --nomodel | ATAC doesn't have control, can't build model | | --shift -75 | Centers on Tn5 insertion site | | --extsize 150 | Smooths signal around cut sites | | --keep-dup all | Tn5 creates duplicate cuts at accessible sites | | -f BAMPE | Uses 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 0.01Broad 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 0.1Batch 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
doneOutput Files
| File | Description | |------|-------------| | _peaks.narrowPeak | Peak locations (BED-like) | | _summits.bed | Peak summit positions | | _peaks.xls | Peak statistics (Excel format) | | _treat_pileup.bdg | Signal track (bedGraph) | | _control_lambda.bdg | Background (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.bedRelated Skills
- read-al
The largest open-source medical AI skill library for OpenClaw.
Other skills on openclaw-medical-skills.
- /aav-vector-design-agent
<!--
Open skill - /adaptyv
Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use
Open skill - /adhd-daily-planner
Time-blind friendly planning, executive function support, and daily structure for ADHD brains. Specializes in realistic time estimation, dopamine-aware task design, and building systems that
Open skill - /aeon
This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations
Open skill - /agent-browser
Browse the web for any task — research topics, read articles, interact with web apps, fill forms, take screenshots, extract data, and test web pages. Use whenever a browser would be useful, not just when the user explicitly asks.
Open skill - /agentd-drug-discovery
<!--
Open skill

