An R pipeline for inference of gene regulatory networks and identification of cell states in RNA-seq data sets. The SCENIC (Single-Cell rEgulatory Network Inference and Clustering) workflow utilizes three separate packages, GENIE3 or GRNBoost2, RcisTarget, and AUCell. A Python implementation of this workflow is faster than this initial R version. See links for pySCENIC. The current version supports human, mouse, and Drosophila melanogaster.
RNA-seq; Molecular interactions, pathways and networks; Gene expression; Transcription factors and regulatory sites
Aibar S, Gonzalez-Blas CB, Moerman T, Huynh-Thu VA, Imrichova H, Hulselmans G, Rambow F, Marine JC, Geurts P, Aerts J, van den Oord J, Atak ZK, Wouters J, Aerts S "SCENIC: single-cell regulatory network inference and clustering." Nat Methods. 2017 Nov;14(11):1083-1086. https://doi.org/10.1038/nmeth.4463
PMID: 28991892
PMCID: PMC5937676
Davie K, Janssens J, Koldere D, De Waegeneer M, Pech U, Kreft Ł, Aibar S, Makhzami S, Christiaens V, Bravo González-Blas C, Poovathingal S, Hulselmans G, Spanier KI, Moerman T, Vanspauwen B, Geurs S, Voet T, Lammertyn J, Thienpont B, Liu S, Konstantinides N, Fiers M, Verstreken P, Aerts S. "A Single-Cell Transcriptome Atlas of the Aging Drosophila Brain." Cell. 2018 Aug 9;174(4):982-998.e20. https://doi.org/10.1016/j.cell.2018.05.057
PMID: 29909982
PMCID: PMC6086935
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