aertslab/CREsted

Bias factorized, base-resolution deep learning models of chromatin accessibility (chromBPNet)

scooby: Modeling multi-modal genomic profiles from DNA sequence at single-cell resolution.

Decima is a Python library to train sequence models on single-cell RNA-seq data.

Transformer for One-Stop Interpretable Cell-type Annotation

Machine learning methods for DNA sequence analysis.

Pipeline to run scE2G

🧬 Generative modeling of regulatory DNA sequences with diffusion probabilistic models 💨

pySCENIC is a lightning-fast python implementation of the SCENIC pipeline (Single-Cell rEgulatory Network Inference and Clustering) which enables biologists to infer transcription factors, gene regulatory networks and cell types from single-cell RNA-seq data.

Command-first ATAC-seq footprinting, motif analysis, and reproducible interactive reports