# Bio Chipseq Peak Annotation

Annotate ChIP-seq peaks to genomic features and genes using ChIPseeker.

- Repository: https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills (3090 stars)
- Category: Engineering
- License: see repository
- Last updated: 2026-07-21
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-chipseq-peak-annotation -g -a claude-code -y`
Codex: `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-chipseq-peak-annotation -g -a codex -y`
Cursor: `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-chipseq-peak-annotation -g -a cursor -y`
Gemini CLI: `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-chipseq-peak-annotation -g -a gemini-cli -y`

## Description

Annotate ChIP-seq peaks to genomic features and genes using ChIPseeker. Assign peaks to promoters, exons, introns, and intergenic regions. Find nearest genes and calculate distance to TSS. Generate annotation plots and statistics. Use when annotating ChIP-seq peaks to genomic features.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

## Version Compatibility

Reference examples tested with: MACS3 3.0+, clusterProfiler 4.10+

Before using code patterns, verify installed versions match. If versions differ:
- R: `packageVersion('<pkg>')` then `?function_name` to verify parameters

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

# Peak Annotation with ChIPseeker

**"Annotate my ChIP-seq peaks to genes"** → Assign peaks to genomic features (promoter, exon, intron, intergenic), find nearest genes, and calculate TSS distances.
- R: `ChIPseeker::annotatePeak(peaks, TxDb=txdb)`

## Load Peaks and Annotations

```r
library(ChIPseeker)
library(TxDb.Hsapiens.UCSC.hg38.knownGene)
library(org.Hs.eg.db)

txdb <- TxDb.Hsapiens.UCSC.hg38.knownGene

# Read peaks from MACS3
peaks <- readPeakFile('sample_peaks.narrowPeak')
```

## Annotate Peaks

**Goal:** Assign each ChIP-seq peak to its nearest gene and genomic feature category.

**Approach:** Use annotatePeak with a TxDb annotation database to classify peaks as promoter, exon, intron, or intergenic and retrieve the nearest gene symbol.

```r
# Annotate with default settings
peak_anno <- annotatePeak(
    peaks,
    TxDb = txdb,
    annoDb = 'org.Hs.eg.db'
)

# View annotation summary
peak_anno
```

## Custom Promoter Definition

```r
# Define promoter region (-3kb to +3kb from TSS)
peak_anno <- annotatePeak(
    peaks,
    TxDb = txdb,
    tssRegion = c(-3000, 3000),  # Promoter definition
    annoDb = 'org.Hs.eg.db'
)
```

## Extract Annotated Data Frame

```r
# Convert to data frame
anno_df <- as.data.frame(peak_anno)

# Key columns: seqnames, start, end, annotation, distanceToTSS, SYMBOL, GENENAME
head(anno_df)

# Export to CSV
write.csv(anno_df, 'annotated_peaks.csv', row.names = FALSE)
```

## Get Genes with Peaks in Promoter

```r
# Filter for promoter peaks
promoter_peaks <- anno_df[grep('Promoter', anno_df$annotation), ]

The rest: https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/blob/HEAD/skills/bio-chipseq-peak-annotation/SKILL.md