Model-based deep embedding for constrained clustering analysis of single cell RNA-seq data

Abstract

Clustering cells based on similarities in gene expression is the first step towards identifying cell types in scRNASeq data. Here the authors incorporate biological knowledge into the clustering step to facilitate the biological interpretability of clusters, and subsequent cell type identification.