bio-atac-seq-deep-learning-atac

Name: bio-atac-seq-deep-learning-atac
Rating: 5 (2 reviews)
Author: bg-szy

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 uno

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Version Compatibility

Reference examples tested with: chrombpnet 0.1.7+, bpnet-lite 0.6+ (DOI 10.5281/zenodo.7011327), 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 an

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