Interpretation of an individual functional genomics experiment guided by massive public data. (December 2018)

• Record Type: Journal Article
• Authors: Lee, Young-suk; Wong, Aaron; Tadych, Alicja; Hartmann, Boris; Park, Christopher; DeJesus, Veronica; Ramos, Irene; Zaslavsky, Elena; Sealfon, Stuart; Troyanskaya, Olga
• Is Part Of: Nature methods. Volume 15:Number 12(2018)
• Page Start: 1049
• Page End: 1052
• Publication Date: 2018-12
• Subjects: Life sciences -- Methodology -- Periodicals; Life sciences -- Research -- Periodicals; Biology -- Methodology -- Periodicals; Biology -- Research -- Periodicals; 570.72
• DOI: 10.1038/s41592-018-0218-5
• Languages: English
• ISSNs: 1548-7091

Abstract

Abstract A key unmet challenge in interpreting omics experiments is inferring biological meaning in the context of public functional genomics data. We developed a computational framework, Your Evidence Tailored Integration (YETI;http://yeti.princeton.edu/ ), which creates specialized functional interaction maps from large public datasets relevant to an individual omics experiment. Using this tailored integration, we predicted and experimentally confirmed an unexpected divergence in viral replication after seasonal or pandemic human influenza virus infection. YETI puts individual -omics experiments in the context of public genomics data by creating an integrated dataset-specific functional network, thus allowing more thorough interpretation of the data.