bio-atac-seq-deep-learning-atac skillA
bio-atac-seq-deep-learning-atac is agent-read markdown (skill) from pku-yuangroup/openai4s: Sequence-based deep learning for ATAC-seq using chromBPNet, BPNet, scBasset, or Enformer. Use when correcting Tn5 bias with neural networks beyond k-mer models, predicting per-base accessibility profiles, scoring in silico variant effects at GWAS or rare-variant SNPs, discovering motifs via DeepLIFT/TF-MoDISco from a trained model, or generating cell-type-specific accessibility predictions for unobserved cell states..
Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.
What the file says
## Version Compatibility Reference examples tested with: chrombpnet 0.1.7+, bpnet-lite 0.6+ (github.com/jmschrei/bpnet-lite), scBasset 0.1.0+ (basenji2 fork), tangermeme 0.1+, tfmodisco-lite 2.2+, DeepLIFT 0.6+, captum 0.7+, tensorflow 2.13+, pytorch 2.1+, kipoi 0.8+. Verify before use: - Python: `pip show <package>` then `help(module.function)` to check signatures - CLI: `<tool> --version` then `<tool> --help` to confirm flags If code throws unexpected errors, introspect the installed package and adapt rather than retrying. Deep-learning tooling evolves rapidly; method papers post 2023 may have superseded reference implementations. # Sequence-Based Deep Learning for ATAC-seq **"Score the effect of a GWAS SNP on chromatin accessibility"** -> Train (or use pre-trained) sequence-to-accessibility CNNs that take 1-5 kb DNA windows and predict per-base Tn5 cleavage profiles. Outputs include: bias-corrected accessibility, single-base mutation effect predictions, and DeepLIFT contribution scores convertible to motifs via TF-MoDISco. - CLI: `chrombpnet pipeline --bigwig signal.bw --bigwig-bias bias.bw ...` …
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How to install
mdr add pku-yuangroup/openai4s/bio-atac-seq-deep-learning-atac@git:20260821.2d1b678mdr add pku-yuangroup/openai4s/bio-atac-seq-deep-learning-atac@sha256:b588803cc1ab6cf3Pin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.
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Source
pku-yuangroup/openai4s · 586 stars · license MIT · pushed 2026-09-23 · branch main
API
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