siVAE: interpretable deep generative models for single cell transcriptomics

This repository includes siVAE, a python package for interpretable deep learning model designed for single cell transcriptomic data as well as additional anaylsis. Main functionality of the package outputs both cell embeddings as well as gene embedding used to interpret the cell embedding. Addiitonal experiments consist of benchmarking against existing methods, analysis for gene embedding space, and applications in gene regulatory network inference,