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bio-clip-seq-binding-site-annotation

bio-clip-seq-binding-site-annotation is a skill for Claude Code, Codex from GPTomics/bioSkills. It costs 142 tokens per session (5,932 once invoked), scanned A, original, MIT.

An annotation workflow that labels CLIP-seq binding sites by their location in RNA, such as a 5′ UTR, coding region, 3′ UTR, intron, splice junction, or non-coding RNA.

In plain words
What is it for?
Use it to summarize where an RNA-binding protein binds and compare its binding across transcript features, repeat elements, and different RNA classes.
Why use it?
A binding site’s RNA feature often changes its biological interpretation. Annotation turns a list of genomic positions into understandable transcript context.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is python rbpmaps/RBPMaps.py \.

not rated 1.2krepo 26d ago A scan 142 tokens original MIT archived

Good fit Use it to summarize where an RNA-binding protein binds and compare its binding across transcript features, repeat elements, and different RNA classes.

Compare 6 skills from other repositories ↓
View source ↗ GPTomics/bioSkills
Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/GPTomics/bioSkills
agentmods
npx agentmods add skills/gptomics/bioskills/binding-site-annotation

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for bio-clip-seq-binding-site-annotation

README.md
[![agentmods](https://agentmods.dev/badge/skills/gptomics/bioskills/binding-site-annotation/github.svg)](https://agentmods.dev/skills/gptomics/bioskills/binding-site-annotation)
Your own site
<a href="https://agentmods.dev/skills/gptomics/bioskills/binding-site-annotation"><img src="https://agentmods.dev/badge/skills/gptomics/bioskills/binding-site-annotation/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for bio-clip-seq-binding-site-annotation

Your own site · 80×15
<a href="https://agentmods.dev/skills/gptomics/bioskills/binding-site-annotation"><img src="https://agentmods.dev/badge/skills/gptomics/bioskills/binding-site-annotation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 142 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 5,932 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00142 $0.05932
Opus 5 $0.00071 $0.02966
Sonnet 5 $0.00028 $0.01186
Haiku 4.5 $0.00014 $0.00593

Measured 7d ago against content hash 1d883906734f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

bio-clip-seq-binding-site-annotation scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

clip-seq/binding-site-annotation/SKILL.md · 329 lines

How it starts

The opening of the file, as written. The whole thing — 329 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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

Read the full file on GitHub · 329 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 7d ago First seen · 329 lines · 142 tokens per session scan A 1d883906734f

Subscribe to this mod's changes

bio-clip-seq-binding-site-annotation is a skill published in the GitHub repository GPTomics/bioSkills (1,199 stars, last pushed 26d ago), licensed MIT. It adds 142 tokens to every session and 5,932 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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