Interpretation of an individual functional genomics experiment guided by massive public data.,Nature Methods

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Interpretation of an individual functional genomics experiment guided by massive public data.
Nature Methods ( IF 36.1 ) Pub Date : 2018-11-26 , DOI: 10.1038/s41592-018-0218-5
Young-Suk Lee _{1,

2,

3} , Aaron K Wong ₄ , Alicja Tadych ₁ , Boris M Hartmann ₅ , Christopher Y Park ₄ , Veronica A DeJesus ₆ , Irene Ramos ₆ , Elena Zaslavsky ₅ , Stuart C Sealfon ₅ , Olga G Troyanskaya _{1,

2,

4}

Affiliation

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.

中文翻译：

在大量公共数据的指导下解释个体功能基因组学实验。

解释组学实验的一个关键未解决的挑战是在公共功能基因组学数据的背景下推断生物学意义。我们开发了一个计算框架，Your Evidence Tailored Integration（YETI；http://yeti.princeton.edu/），它从与单个组学实验相关的大型公共数据集创建专门的功能相互作用图。利用这种定制的整合，我们预测并通过实验证实了季节性或大流行性人类流感病毒感染后病毒复制的意外差异。

更新日期：2018-12-10

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