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bio-atac-seq-footprinting skillA

bio-atac-seq-footprinting is agent-read markdown (skill) from pku-yuangroup/openai4s: Detect transcription factor binding footprints in ATAC-seq using TOBIAS, HINT-ATAC, Wellington, or scprinter. Use when identifying bound TF sites within accessible regions, correcting Tn5 insertion bias before footprinting, choosing between cleavage-based and aggregate-based footprinters, or comparing differential TF activity between conditions..

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## Version Compatibility

Reference examples tested with: TOBIAS 0.16+, RGT HINT-ATAC 1.0.2+, Wellington (pyDNase) 0.3+, scprinter 0.1+, samtools 1.19+, bedtools 2.31+, pyBigWig 0.3+, MEME suite 5.5+.

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# TF Footprinting

**"Identify TF binding footprints in my ATAC-seq data"** -> Detect short DNA stretches (typically 6-20 bp) of reduced Tn5 cleavage within accessible regions, where a bound TF physically protects DNA. Requires (1) Tn5 sequence-bias correction, (2) per-base footprint scoring, (3) motif-anchored detection.

- CLI: `TOBIAS ATACorrect` -> `TOBIAS ScoreBigwig` (formerly `FootprintScores`) -> `TOBIAS BINDetect`
- CLI: `rgt-hint footprinting --atac-seq` (HINT-ATAC, single-step)
- CLI: `wellington_footprints.py` (legacy DNase, adapted for ATAC)
- Python: `scprinter` (multi-scale, single-cell aware; Hu 2025 Nature)
…

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Source

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pku-yuangroup/openai4s · 586 stars · license MIT · pushed 2026-09-23 · branch main

API

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