GeNets: a unified web platform for network-based genomic analyses
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Author(s)
Li, Taibo
Kim, April
Rosenbluh, Joseph
Horn, Heiko
Greenfeld, Liraz
An, David
Zimmer, Andrew
Liberzon, Arthur
Bistline, Jon
Natoli, Ted
Date Issued
June 2018
Journal
Nature Methods
Publisher
Nature Publishing Group
Citation
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)
Version
Author's final manuscript
Abstract
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.
MIT Department
Massachusetts Institute of Technology. Department of Biology
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1038/s41592-018-0039-6
