# Bio Atac Seq Footprinting

Detect transcription factor binding sites through footprinting analysis in ATAC-seq...

- Repository: https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills (3090 stars)
- Category: Design
- License: see repository
- Last updated: 2026-07-21
- Runs scripts: yes, review before use

## Install

Claude Code: `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-atac-seq-footprinting -g -a claude-code -y`
Codex: `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-atac-seq-footprinting -g -a codex -y`
Cursor: `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-atac-seq-footprinting -g -a cursor -y`
Gemini CLI: `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-atac-seq-footprinting -g -a gemini-cli -y`

## Description

Detect transcription factor binding sites through footprinting analysis in ATAC-seq data using TOBIAS. Use when identifying TF occupancy patterns within accessible regions, as TF binding protects DNA from Tn5 cutting.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

## Version Compatibility

Reference examples tested with: bedtools 2.31+, matplotlib 3.8+, numpy 1.26+, pandas 2.2+, pyBigWig 0.3+, samtools 1.19+

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

If code throws ImportError, AttributeError, or TypeError, introspect the installed
package and adapt the example to match the actual API rather than retrying.

# TF Footprinting

**"Identify TF binding footprints in my ATAC-seq data"** → Detect protected DNA regions within accessible chromatin where bound transcription factors block Tn5 insertion.
- CLI: `TOBIAS ATACorrect` → `TOBIAS FootprintScores` → `TOBIAS BINDetect`

## TOBIAS Workflow

**Goal:** Identify transcription factor binding footprints within accessible chromatin regions.

**Approach:** Correct Tn5 insertion bias, compute per-base footprint scores, then detect bound/unbound TF motif sites using the three-step TOBIAS pipeline.

```bash
# 1. Correct Tn5 bias
tobias ATACorrect \
    --bam sample.bam \
    --genome genome.fa \
    --peaks peaks.bed \
    --outdir corrected/ \
    --cores 8

# 2. Calculate footprint scores
tobias FootprintScores \
    --signal corrected/sample_corrected.bw \
    --regions peaks.bed \
    --output footprints.bw \
    --cores 8

# 3. Bind TF motifs
tobias BINDetect \
    --motifs JASPAR_motifs.pfm \
    --signals footprints.bw \
    --genome genome.fa \
    --peaks peaks.bed \
    --outdir bindetect_output/ \
    --cores 8
```

## TOBIAS Differential Footprinting

**Goal:** Compare TF binding between two conditions to identify regulators with differential activity.

**Approach:** Provide two bias-corrected signal tracks to BINDetect, which scores each motif site for differential binding between conditions.

The rest: https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/blob/HEAD/skills/bio-atac-seq-footprinting/SKILL.md