ACTIONet single-cell analysis framework
chrombpnet predicts chromatin accessibility from sequence
Kundaje lab edits to Scott Lundberg's unified approach to explain the output of any machine learning model.
Deep RegulAtory GenOmic Neural Networks (DragoNN)
keras Accessibility Models (kerasAC)
Generate genome-wide classification and regression labels for DNA accessibility data.
DeepLIFT (Deep Learning Important FeaTures)
Keras Deep Learning for Genomics layers
SAM file alignment statistics at the read level
Compute deep learning embeddings for narrowPeak files; compute pairwise distance between embeddings and cluster with tSNE
Simulations of DNA for the Dragonn Package