bio-atac-seq-enhancer-gene-linking skillA
bio-atac-seq-enhancer-gene-linking is agent-read markdown (skill) from pku-yuangroup/openai4s: Predict enhancer-gene regulatory connections from ATAC-seq using ABC, ENCODE-rE2G, HiChIP, or Cicero. Use when linking distal enhancers to target genes, choosing between contact-aware (ABC, ENCODE-rE2G), accessibility-only (Cicero), and orthogonal (HiChIP H3K27ac, EpiMap) approaches, validating predictions against CRISPRi-FlowFISH gold-standard, or building cell-type-specific regulatory maps for fine-mapping or therapeutic target discovery..
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What the file says
## Version Compatibility
Reference examples tested with: ABC-Enhancer-Gene-Prediction 0.2.2+ (Engreitz lab), ENCODE-rE2G v1.0+ (EngreitzLab), Cicero 1.20+, GenomicInteractions 1.36+, FitHiChIP 9.1+, HiC-Pro 3.1+, FAN-C 0.9+, MACS3 3.0+, samtools 1.19+, bedtools 2.31+.
Verify before use:
- CLI: `<tool> --version` then `<tool> --help` to confirm flags
- R: `packageVersion('<pkg>')` then `?function_name` to verify parameters
- Python: `pip show <package>` then `help(module.function)` to check signatures
If code throws unexpected errors, introspect the installed package and adapt rather than retrying.
# Enhancer-Gene Linking
**"Which gene does this distal accessible region regulate?"** -> Predict the enhancer's target gene using a model that combines accessibility activity, 3D contact frequency, and (optionally) sequence-based chromatin predictions. Output is a per-(enhancer, gene) score that can be thresholded for high-confidence calls.
- CLI: ABC pipeline (`run.neighborhoods.py`, `predict.py` from Engreitz lab)
- CLI: ENCODE-rE2G (Snakemake-based; ENCODE 4 enhancer-gene standard)
- R: Cicero (ATAC-only; covered in atac-seq/co-accessibility)
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How to install
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Source
pku-yuangroup/openai4s · 586 stars · license MIT · pushed 2026-09-23 · branch main
API
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