Portal de Periódicos da CAPES

SCENIC: single-cell regulatory network inference and clustering

2017; Nature Portfolio; Volume: 14; Issue: 11 Linguagem: Inglês

10.1038/nmeth.4463

1548-7105

Sara Aibar, Carmen Bravo González‐Blas, Thomas Moerman, Vân Anh Huynh‐Thu, Hana Imrichová, Gert Hulselmans, Florian Rambow, Jean‐Christophe Marine, Pierre Geurts, Jan Aerts, Joost van den Oord, Zeynep Kalender Atak, Jasper Wouters, Stein Aerts,

Cell Image Analysis Techniques

SCENIC enables simultaneous regulatory network inference and robust cell clustering from single-cell RNA-seq data. We present SCENIC, a computational method for simultaneous gene regulatory network reconstruction and cell-state identification from single-cell RNA-seq data ( http://scenic.aertslab.org ). On a compendium of single-cell data from tumors and brain, we demonstrate that cis-regulatory analysis can be exploited to guide the identification of transcription factors and cell states. SCENIC provides critical biological insights into the mechanisms driving cellular heterogeneity.