Agent skill

bio-chipseq-peak-annotation

Annotates ChIP-seq peaks to genomic features, nearest genes, ENCODE candidate cis-regulatory elements (cCREs), and regulatory domains. Uses ChIPseeker (R), HOMER annotatePeaks.pl (CLI), pyranges (Python), GREAT/rGREAT (regulatory domain gene-set enrichment), ChIP-Enrich (locus-length-adjusted), ENCODE SCREEN cCRE classification (PLS/pELS/dELS/CTCF-only/DNase-H3K4me3), and ENCODE-rE2G for cell-type-specific enhancer-gene linking. Handles nearest-TSS vs host-gene ambiguity, promoter window definition, and feature priority. Use when assigning genomic context to peaks, linking enhancer peaks to ta

BioTender-maxgithub.com/BioTender-maxGitHub ↗
claude-codeships scriptsNOASSERTION
Install
npx skills add BioTender-max/awesome-bio-agent-skills --skill peak-annotation --agent claude-code

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

Facts
Files in the skill folder: 4
SKILL.md size: 18 KB
Bundled scripts: yes
Path: skills/bioskills/peak-annotation/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 135
Language: Python

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: ChIPseeker 1.38+, GenomicFeatures 1.54+, rtracklayer 1.62+, HOMER 4.11+, rGREAT 2.4+, chipenrich 2.26+, pyranges 0.0.129+, pandas 2.2+. ENCODE cCRE registry expanded to 2.35M human and 927k mouse elements (Nature 2025; Vu Ernst expansion). SCREEN web app at screen.encodeproject.org provides browser access; ENCODE provides bed files for batch annotation. # Peak Annotation **"What genes and regulatory elements do my peaks correspond to?"** -> Assign each peak to a genomic feature (promoter, exon, intron, intergenic), its target gene (via nearest-TSS or host-gene), and where applicable an ENCODE cCRE class (PLS/pELS/dELS/CTCF-only/DNase-H3K4me3). - R (gene-feature): `ChIPseeker::annotatePeak(peaks, TxDb=txdb)` - CLI (gene-feature): `annotatePeaks.pl peaks.bed hg38 -gtf annotation.gtf` - Python (custom): pyranges + pandas - R (cCRE classification): intersect peaks with ENCODE cCRE BED from SCREEN - R (gene-set enrichment): `rGREAT::great()` or `chipenrich::chipenrich()` The single biggest source of misinterpretation is the **nearest-TSS vs host-gene** distinction (see below). For enhancer-driven biology, ENCODE-rE2G or ABC (in at

What's inside
Steps it walks through
  1. Version Compatibility
  2. Choosing an Annotation Approach
  3. Nearest-TSS vs Host-Gene Convention
  4. Choosing per Biology
  5. Coordinate Systems and TSS
  6. ChIPseeker (R)
  7. HOMER annotatePeaks.pl (CLI)
  8. ENCODE cCRE Classification
  9. GREAT / rGREAT (Regulatory Domain Gene-Set Enrichment)
  10. ChIP-Enrich (Locus-Length-Adjusted Gene-Set Enrichment)
  11. ENCODE-rE2G (Modern Enhancer-Gene Linking)
  12. Per-Tool Failure Modes
  13. ChIPseeker -- TxDb / annoDb genome mismatch
  14. ChIPseeker -- Default overlap='TSS' decouples gene from feature
Ships with 3 files
  • examples/annotate_peaks.R
  • examples/annotate_peaks.py
  • usage-guide.md
Commands it runs
Standard genome (HOMER's installed annotation)
annotatePeaks.pl peaks.bed hg38 > annotated.txt
Custom GTF (overrides HOMER's default)
annotatePeaks.pl peaks.bed hg38 -gtf genes.gtf > annotated.txt
Without installed genome, GTF only
annotatePeaks.pl peaks.bed none -gtf genes.gtf > annotated.txt
Generate annotation statistics
annotatePeaks.pl peaks.bed hg38 -gtf genes.gtf -annStats stats.txt > annotated.txt
Download ENCODE cCRE BED from SCREEN (hg38)
wget https://api.wenglab.org/screen_v13/screen_human_ccres_simple.bed.gz
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About this skill
What does the bio-chipseq-peak-annotation skill do?

Annotates ChIP-seq peaks to genomic features, nearest genes, ENCODE candidate cis-regulatory elements (cCREs), and regulatory domains. Uses ChIPseeker (R), HOMER annotatePeaks.pl (CLI), pyranges (Python), GREAT/rGREAT (regulatory domain gene-set enrichment), ChIP-Enrich (locus-length-adjusted), ENCODE SCREEN cCRE classification (PLS/pELS/dELS/CTCF-only/DNase-H3K4me3), and ENCODE-rE2G for cell-type-specific enhancer-gene linking. Handles nearest-TSS vs host-gene ambiguity, promoter window definition, and feature priority. Use when assigning genomic context to peaks, linking enhancer peaks to ta

How do I install it?

Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill peak-annotation --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 BioTender-max/awesome-bio-agent-skills, a repository with 135 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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