GeNets: a unified web platform for network-based genomic analyses
Author(s)Li, Taibo; Kim, April; Rosenbluh, Joseph; Horn, Heiko; Greenfeld, Liraz; An, David; Zimmer, Andrew; Liberzon, Arthur; Bistline, Jon; Natoli, Ted; Li, Yang; Tsherniak, Aviad; Narayan, Rajiv; Subramanian, Aravind; Liefeld, Ted; Wong, Bang; Thompson, Dawn; Calvo, Sarah; Carr, Steve; Boehm, Jesse; Jaffe, Jake; Mesirov, Jill; Hacohen, Nir; Regev, Aviv; Lage, Kasper; ... Show more Show less
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Functional genomics networks are widely used to identify unexpected pathway relationships in large genomic datasets. However, it is challenging to compare the signal-to-noise ratios of different networks and to identify the optimal network with which to interpret a particular genetic dataset. We present GeNets, a platform in which users can train a machine-learning model (Quack) to carry out these comparisons and execute, store, and share analyses of genetic and RNA-sequencing datasets.
DepartmentMassachusetts Institute of Technology. Department of Biology; Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Nature Publishing Group
Li, Taibo et al. “GeNets: a Unified Web Platform for Network-Based Genomic Analyses.” Nature Methods 15, 7 (June 2018): 543–546 © 2018 The Author(s)
Author's final manuscript