Binding Site Annotation

What the source does

• FilesystemNone observedNo reads or writes in the source
• NetworkNone observedNo outbound calls in the source
• ShellNone observedNo commands run in the source
• DependenciesPinnedNothing floats
• SecretsNone foundNo keys in source

Five audit layers

Gates applied: no behavioural pass.

Audit 0.4.1 · source sha c8c1fc3a2b13 · 19 Oct 2026Report an issue or request a re-scan

• PublisherGPTomics GitHub organizationOwner of the repository this skill is read from
• Source folderGPTomics/bioSkills/clip-seq/binding-site-annotationThe exact folder we audited
• LicenceMITAs the repository states it
• Commit pinned for this verdictc8c1fc3a2b13A new audit runs when the source changes
• Repository statusArchivedLast push 65 days ago
• Sandboxed runNot runSkills are read, not executed; layer L4 is skipped

Its description: Annotate CLIP-seq peaks or crosslink sites to RNA features (5'UTR, CDS, 3'UTR, intron, splice junction, snoRNA, tRNA, ncRNA, repeat elements) with ChIPseeker, RCAS, RBP-Maps (Yeo splicing regulatory maps), and bedtools,…

---
name: bio-clip-seq-binding-site-annotation
description: Annotate CLIP-seq peaks or crosslink sites to RNA features (5'UTR, CDS, 3'UTR, intron, splice junction, snoRNA, tRNA, ncRNA, repeat elements) with ChIPseeker, RCAS, RBP-Maps (Yeo splicing regulatory maps), and bedtools, applying feature-priority hierarchies, transcript-context resolution, and metagene aggregation. Use when characterizing where in transcripts an RBP binds, comparing peak distribution across regions, generating splicing-regulatory maps relative to alternative-splicing events, or distinguishing exonic vs intronic vs UTR binding.
tool_type: mixed
primary_tool: ChIPseeker
---

## Version Compatibility

Reference examples tested with: ChIPseeker 1.40+, RCAS 1.30+, GenomicFeatures 1.56+, GenomicRanges 1.56+, rbp-maps (Yeo github), bedtools 2.31+, pybedtools 0.10+, pyranges 0.0.129+.

Before using code patterns, verify installed versions match. If versions differ:
- R: `packageVersion('<pkg>')` then `?function_name` to verify parameters
- Python: `pip show <package>` then `help(module.function)` to check signatures
- CLI: `<tool> --version` then `<tool> --help` to confirm flags

If code throws unexpected errors, introspect the installed package and adapt the example to match the actual API rather than retrying. ChIPseeker 1.40+ changed the priority defaults; verify the priority vector before pipelining.

# Binding Site Annotation

**"Annotate where in transcripts my RBP binds"** -> Map CLIP peaks or single-nucleotide crosslink sites to RNA features and report the per-feature distribution. The interpretation is RBP-class-specific: splicing factors (PTBP1, U2AF2, RBFOX) bind intron-exon junctions; mRNA-stability regulators (HuR, PUM2) bind 3' UTRs; translation factors (EIF3J, RPS19) bind 5' UTRs and CDS; and small-ncRNA-binding RBPs (NSUN2 tRNAs, LARP7 7SK, TROVE2 Y-RNAs) bind specific non-coding transcripts. A correct annotation pipeline (a) resolves overlapping features by priority, (b) preserves transcript-isoform context, (c) generates metagene distributions, and (d) flags repeat-element overlap separately.

- R (peak-level, fast): `ChIPseeker::annotatePeak(peaks, TxDb=txdb, level='gene', tssRegion=c(-100,100))` then `plotAnnoPie(anno)`
- R (transcript-level with RNA-specific regions): RCAS `runReport(queryRegions=peaks, gffData=gencode_gtf, genomeVersion='hg38')`
- CLI (regions only): `bedtools intersect -s -wa -wb -a peaks.bed -b features.bed` (manual hierarchy)
- R (splicing-regulatory map for splice factors): RBP-Maps (`yeolab/rbp-maps`) generates the 1400 nt vectorized cassette-exon map used in Yeo lab ENCODE papers
- CLI (metagene aggregation): `deepTools computeMatrix` or RSeQC `geneBody_coverage.py` for read profiles

The Yeo lab convention for ENCODE eCLIP: ChIPseeker for global region distribution + RBP-Maps for position-resolved splicing context + custom analysis for repeat-element overlap. ChIPseeker alone over-counts intronic binding because TSS-region default extends too far for RNA features.

## Algorithmic Taxonomy

| Tool | Input | Annotation level | Feature priority | Output | Strength | Fails when |
|------|-------|------------------|------------------|--------|----------|------------|
| ChIPseeker (R) | Peak BED + TxDb | Gene-level or transcript-level | Promoter > 5' UTR > 3' UTR > Exon > Intron > Intergenic | Per-peak annotation + pie chart + distance-to-TSS | Mature, widely used, fast | TSS-region default `c(-3000, 3000)` over-extends; promoter category meaningless for RNA |
| RCAS (R) | Peak BED + GFF | Transcript-level | Customizable | HTML report + per-region table | RNA-specific design; ncRNA-aware | Slow; HTML-heavy; less actively maintained |
| RBP-Maps (Yeo) | eCLIP BAM + alternative splicing event tables | Splice junction-level | NA (positional metagene) | Splicing regulatory map (1400nt vector around cassette exon) | The standard for splicing-factor CLIP analysis | Splicing-only; not for 3' UTR or ncRNA binders |
| HOMER annotatePeaks.pl | Peak BED | Gene-level | Promoter > UTR > Exon > Intron > Intergenic | Annotation TSV | Familiar from ChIP-seq | Same TSS issue as ChIPseeker; less RNA-aware |
| bedtools intersect | Peak BED + feature BED | User-defined | User-defined | Per-feature overlap | Most flexible | Manual hierarchy logic must be written |
| pyranges (Python) | Peak BED + GTF | Customizable | User-defined | DataFrame | Fast, pythonic, scriptable | Hand-written priority logic |
| pybedtools | Peak BED + GTF | Customizable | User-defined | iterators | Flexible, scripted | Same as pyranges |
| Peakhood (Uhl 2022) | Peak BED + transcripts | Transcript context | NA | Per-peak transcript context | Resolves transcript-isoform ambiguity | Specialized; not a global region tool |

Methodology evolves; verify the GTF source (GENCODE preferred over Ensembl for human; both have feature differences) and the priority hierarchy against published RBP literature.

## Critical Choice: Annotation Hierarchy

RNA features are nested and overlapping. A 3' UTR peak is ALSO in an exon; an intronic peak near a splice site is ALSO in a transcribed-but-spliced region. Without a priority hierarchy the same peak gets counted multiple times.

**Standard CLIP hierarchy (most-specific first):**

1. **3' UTR** (specific to mature mRNA biology)
2. **5' UTR**
3. **CDS** (coding sequence)
4. **Exon** (catch-all for non-UTR exonic)
5. **Splice site** (within 50 nt of donor/acceptor; key for splicing factors)
6. **Intron**
7. **Promoter** (within 1 kb of TSS; usually not relevant for RNA-binding)
8. **5' flanking** / **3' flanking** (within 1 kb of gene)
9. **ncRNA** (lncRNA, snoRNA, snRNA, miRNA host)
10. **Repeat element** (Alu, LINE, LTR, SINE) - separate axis from above
11. **Intergenic**

ChIPseeker's default `level='gene'` reports the FIRST hit by priority. For CLIP, set `level='transcript'` and explicitly customize `tssRegion=c(-100, 100)` (default `c(-3000, 3000)` is for ChIP).

**Why CLIP needs the tight TS

Excerpt, first 6,000 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.

git clone https://github.com/YeoLab/rbp-maps

git clone https://github.com/GPTomics/bioSkills
git -C bioSkills checkout c8c1fc3a2b13

Works in

1. 2026-10-19
   ✓SAFE B 89 / 100

   first audit · source c8c1fc3a2b13

Questions about Binding Site Annotation

• github.com/GPTomics/bioSkills/tree/main/clip-seq/binding-site-an — the audited source at commit c8c1fc3a2b13 and every finding aboveObserved · 19 Oct 2026

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