Interpretation of an individual functional genomics experiment guided by massive public data

Young suk Lee, Aaron K. Wong, Alicja Tadych, Boris M. Hartmann, Christopher Y. Park, Veronica A. DeJesus, Irene Ramos, Elena Zaslavsky, Stuart C. Sealfon, Olga G. Troyanskaya

Research output: Contribution to journalArticle

2 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)1049-1052
Number of pages4
JournalNature Methods
Volume15
Issue number12
DOIs
StatePublished - Dec 1 2018

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Biochemistry
  • Molecular Biology
  • Cell Biology

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    Lee, Y. S., Wong, A. K., Tadych, A., Hartmann, B. M., Park, C. Y., DeJesus, V. A., Ramos, I., Zaslavsky, E., Sealfon, S. C., & Troyanskaya, O. G. (2018). Interpretation of an individual functional genomics experiment guided by massive public data. Nature Methods, 15(12), 1049-1052. https://doi.org/10.1038/s41592-018-0218-5