genomic-region-annotation-integration

genomic-region-annotation-integration is a skill for Claude Code, Codex from HolobiomicsLab/asb-skill-collections. It costs 70 tokens per session (1,506 once invoked), scanned A, original, Apache-2.0.

A footprint-scoring step for ATAC-seq data that measures small gaps in DNA-cutting signal inside accessible genome regions. ATAC-seq identifies open chromatin, and these gaps can indicate where transcription factors are bound.

In plain words
What is it for?
Use it after ATACorrect has produced a bias-corrected bigWig file and after peaks or other accessible regions have been defined.
Why use it?
Raw cutting patterns can be biased by the sequencing enzyme and may obscure binding footprints. Scoring the corrected signal gives a base-level measure of possible transcription-factor occupancy.

Skill for Claude CodeCodex

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

Good fit Use it after ATACorrect has produced a bias-corrected bigWig file and after peaks or other accessible regions have been defined.

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Install with agentmods
npx agentmods add skills/holobiomicslab/asb-skill-collections/genomic-region-annotation-integration
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add HolobiomicsLab/asb-skill-collections --skill genomic-region-annotation-integration
Clone the repo
git clone --depth 1 https://github.com/HolobiomicsLab/asb-skill-collections

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 genomic-region-annotation-integration

README.md
[![agentmods](https://agentmods.dev/badge/skills/holobiomicslab/asb-skill-collections/genomic-region-annotation-integration/github.svg)](https://agentmods.dev/skills/holobiomicslab/asb-skill-collections/genomic-region-annotation-integration)
Your own site
<a href="https://agentmods.dev/skills/holobiomicslab/asb-skill-collections/genomic-region-annotation-integration"><img src="https://agentmods.dev/badge/skills/holobiomicslab/asb-skill-collections/genomic-region-annotation-integration/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 genomic-region-annotation-integration

Your own site · 80×15
<a href="https://agentmods.dev/skills/holobiomicslab/asb-skill-collections/genomic-region-annotation-integration"><img src="https://agentmods.dev/badge/skills/holobiomicslab/asb-skill-collections/genomic-region-annotation-integration.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 70 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,506 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00070 $0.01506
Opus 5 $0.00035 $0.00753
Sonnet 5 $0.00014 $0.00301
Haiku 4.5 $0.00007 $0.00151

Measured 9d ago against content hash c720c5de6201, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

genomic-region-annotation-integration 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 9d 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.

collections/epigenomics/v1/skills/genomic-region-annotation-integration/SKILL.md · 96 lines

How it starts

The opening of the file, as written. The whole thing — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Reconstruct the footprint scoring step that converts bias-corrected ATAC-seq signal into per-base footprint scores

Summary

This skill converts bias-corrected ATAC-seq insertion signal into footprint scores by measuring Tn5 insertion depletion patterns within accessible chromatin regions. It quantifies the magnitude of transcription factor binding footprints at base-pair resolution for downstream differential binding and visualization.

When to use

Apply this skill after bias-correcting ATAC-seq cutsite signal (via ATACorrect) when you have a bias-corrected bigWig file and need to compute per-position footprint scores within defined accessible regions (peaks, called footprints, or regulatory regions) to detect and quantify transcription factor occupancy through characteristic insertion depletion.

When NOT to use

  • Input bigWig is uncorrected or not yet bias-corrected; use ATACorrect first.
  • You have no defined accessible chromatin regions; define peaks or regulatory regions before scoring.
  • The goal is only bulk chromatin accessibility quantification without transcription factor binding inference; standard peak calling and quantification suffices.

Inputs

  • bias-corrected bigWig file (from ATACorrect)
  • BED file of accessible genomic regions (ATAC-seq peaks or footprint regions)

Outputs

  • footprint-score bigWig file (per-base footprint scores across input regions)

How to apply

Load the bias-corrected bigWig file (output from ATACorrect) and supply a BED file of accessible genomic regions where footprint scoring should occur. Use TOBIAS ScoreBigwig to measure signal depletion at each base within those regions, generating a bigWig output where each position reflects the magnitude of observed insertion depletion. The tool operates on the principle that protein-bound sites show visible depletion of Tn5 insertions, quantifying this depletion as a footprint score. Validate the output bigWig for correct format (valid header, coordinate ranges), non-zero score distributions, and consistency with input region boundaries.

Read the full file on GitHub · 96 lines

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. 9d ago First seen · 96 lines · 70 tokens per session scan A c720c5de6201

Subscribe to this mod's changes

genomic-region-annotation-integration is a skill published in the GitHub repository HolobiomicsLab/asb-skill-collections (15 stars, last pushed yesterday), licensed Apache-2.0. It adds 70 tokens to every session and 1,506 once invoked, about $0.0003 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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