The main repository for ACTIVA: realistic single-cell RNA-seq generation with automatic cell-type identification using introspective variational autoencoders

R package: {rfca} Random forest-based cell annotation methods for scRNAseq analysis. {rfca} contains methods which identifies cell types using machine learning trained on a diversity of cell types, without the need for a labelled training dataset. It also allows you to train your own cell prediction models with your own labels (cell type, subtyp…

Repo linked to our recent publication in Science Advances