Agent skill · Data & Analytics

atac-footprinting

This skill performs transcription factor (TF) footprint analysis using TOBIAS on ATAC-seq data. It corrects Tn5 sequence bias, quantifies TF occupancy at motif sites, generates footprint scores, and optionally compares differential TF binding across conditions.

majiayu000github.com/majiayu000GitHub ↗
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill 28-atacseq-footprint --agent claude-code

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

Facts
Files in the skill folder: 2
SKILL.md size: 5 KB
Bundled scripts: none
Path: skills/analysis/28-atacseq-footprint/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# ATAC-seq Footprint Analysis using TOBIAS ## 1. Overview This skill performs TF footprint detection and optional differential TF binding analysis using TOBIAS. It identifies true TF occupancy by modeling depletion of Tn5 insertions at motif cores. Main steps include: - Refer to the **Inputs & Outputs** section to check required inputs and set up the output directory structure. - **Always prompt user** for genome assembly used. - **Always prompt user** if other required files are missing. - Tn5 bias correction with ATACorrect. - Motif scanning. - Footprint scoring. - Binding detection with BINDetect. - Aggregate footprint visualization. --- ## 2. When to use this skill Use this skill when you need to identify transcription factor occupancy using ATAC-seq data. It is suitable for: - Mapping TF binding events without ChIP-seq. - Comparing TF footprint strength between conditions or cell types. - Identifying which TFs gain or lose binding activity during differentiation or perturbation. - Supporting integrative regulatory analyses with RNA-seq, ChIP-seq, or chromatin conformation data. Recommended data requirements: - Biological replicates are preferred (≥2 per condition). - ≥30M pair

What's inside
Steps it walks through
  1. 1. Overview
  2. 2. When to use this skill
  3. 3. Inputs & Outputs
  4. Inputs
  5. Outputs
  6. 4. Decision Tree
  7. Step 1: Validate inputs
  8. Step 2: Tn5 Bias correction
  9. Step 3: Motif scanning
  10. Step 4: Footprint scoring
  11. Step 5: Binding detection
  12. Step 6: Aggregate plots
  13. Advanced Usage
Ships with 1 file
  • metadata.json
Commands it runs
ATAC_footprint_analysis/
motifs.bed                  # motif genomic coordinates
scan.log
score.log
motif_activity.txt          # differential TF activity (if applicable)
bindetect.log
aggregate.log
logs/ # all logs
temp/ # intermediate files
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About this skill
What does the atac-footprinting skill do?

This skill performs transcription factor (TF) footprint analysis using TOBIAS on ATAC-seq data. It corrects Tn5 sequence bias, quantifies TF occupancy at motif sites, generates footprint scores, and optionally compares differential TF binding across conditions.

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill 28-atacseq-footprint --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 majiayu000/claude-skill-registry, a repository with 534 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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