GSE114557
cisTopic: cis-regulatory topic modelling on single-cell ATAC-seq data
We present cisTopic, a probabilistic framework to simultaneously discover co-accessible enhancers and stable cell states from sparse single-cell?epigenomics?data (http://github.com/aertslab/cistopic). On a compendium of single-cell ATAC-seq datasets from differentiating hematopoietic cells, brain, and transcription-factor perturbation dynamics, we demonstrate that topic modelling can be exploited for a robust identification of cell types, enhancers, and relevant transcription factors. cisTopic provides insight into the mechanisms underlying regulatory heterogeneity within cell populations. Overall design: Time series scATAC-seq (Fluidigm C1) and bulk OmniATAC-seq of SOX10 knockdown-induced phenotype switching in two melanoma cell lines. ChIP-seq of H3K27Ac on four melanoma cell lines.