Agent skill

bio-chipseq-peak-calling

ChIP-seq peak calling using MACS3 (or MACS2). Call narrow peaks for transcription factors or broad peaks for histone modifications. Supports input control, fragment size modeling, and various output formats including narrowPeak and broadPeak BED files. Use when calling peaks from ChIP-seq alignments.

FreedomIntelligencegithub.com/FreedomIntelligenceGitHub ↗
claude-codeships scripts
Install
npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-chipseq-peak-calling --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 3
SKILL.md size: 8 KB
Bundled scripts: yes
Path: skills/bio-chipseq-peak-calling/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 2,909
Language: Python
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

## Version Compatibility Reference examples tested with: MACS2 2.2+, MACS3 3.0+ 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. # Peak Calling with MACS3 **"Call peaks from my ChIP-seq data"** → Identify significantly enriched regions (narrow peaks for TFs, broad peaks for histone marks) by comparing IP signal to input control. - CLI: `macs3 callpeak -t chip.bam -c input.bam -f BAM -g hs -n sample` MACS3 is the actively developed successor to MACS2. Commands are identical except the binary name. MACS2 is in maintenance mode. ## Basic Peak Calling **Goal:** Call enriched regions from ChIP-seq alignments with input control normalization. **Approach:** Compare treatment BAM signal against input control using MACS3 local Poisson model. ```bash # Call peaks with input control (recommended) macs3 callpeak -t chip.bam -c input.bam -f BAM -g hs -n sample --outdir peaks/ # For MACS2 (legacy), replace 'macs3' with 'macs2' - syntax is identi

What's inside
Steps it walks through
  1. Version Compatibility
  2. Basic Peak Calling
  3. Without Input Control
  4. Narrow Peaks (TF, H3K4me3, H3K27ac)
  5. Broad Peaks (H3K36me3, H3K27me3, H3K9me3)
  6. Paired-End Data
  7. Multiple Replicates
  8. Custom Genome Size
  9. Common Genome Sizes
  10. Fixed Fragment Size
  11. Generate Signal Tracks
  12. Local Lambda for Broad Marks
  13. Cutoff Analysis
  14. Output Files
Ships with 2 files
  • examples/macs3_peak_calling.sh
  • usage-guide.md
Commands it runs
Call peaks with input control (recommended)
macs3 callpeak -t chip.bam -c input.bam -f BAM -g hs -n sample --outdir peaks/
For MACS2 (legacy), replace 'macs3' with 'macs2' - syntax is identical
Not recommended, but possible
macs3 callpeak -t chip.bam -f BAM -g hs -n sample --outdir peaks/
macs3 callpeak \
MACS3 uses BAMPE format for paired-end
Pool replicates (MACS3 handles internally)
For non-model organisms or custom genomes
If modeling fails or for ATAC-seq
More from OpenClaw-Medical-Skills
All skills →
About this skill
What does the bio-chipseq-peak-calling skill do?

ChIP-seq peak calling using MACS3 (or MACS2). Call narrow peaks for transcription factors or broad peaks for histone modifications. Supports input control, fragment size modeling, and various output formats including narrowPeak and broadPeak BED files. Use when calling peaks from ChIP-seq alignments.

How do I install it?

Run `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-chipseq-peak-calling --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From FreedomIntelligence/OpenClaw-Medical-Skills, a repository with 2,909 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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