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.
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.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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
- 1. Overview
- 2. When to use this skill
- 3. Inputs & Outputs
- Inputs
- Outputs
- 4. Decision Tree
- Step 1: Validate inputs
- Step 2: Tn5 Bias correction
- Step 3: Motif scanning
- Step 4: Footprint scoring
- Step 5: Binding detection
- Step 6: Aggregate plots
- Advanced Usage
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
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.
