| Literature DB >> 30962623 |
Carmen Bravo González-Blas1,2, Liesbeth Minnoye1,2, Dafni Papasokrati1,2, Sara Aibar1,2, Gert Hulselmans1,2, Valerie Christiaens1,2, Kristofer Davie1,2, Jasper Wouters1,2, Stein Aerts3,4.
Abstract
We present cisTopic, a probabilistic framework used to simultaneously discover coaccessible enhancers and stable cell states from sparse single-cell epigenomics data ( http://github.com/aertslab/cistopic ). Using a compendium of single-cell ATAC-seq datasets from differentiating hematopoietic cells, brain and transcription factor perturbations, we demonstrate that topic modeling can be exploited for robust identification of cell types, enhancers and relevant transcription factors. cisTopic provides insight into the mechanisms underlying regulatory heterogeneity in cell populations.Entities:
Mesh:
Year: 2019 PMID: 30962623 PMCID: PMC6517279 DOI: 10.1038/s41592-019-0367-1
Source DB: PubMed Journal: Nat Methods ISSN: 1548-7091 Impact factor: 28.547