Integrative framework for identification of key cell identity genes uncovers determinants of ES cell identity and homeostasis.

ABSTRACT: Identification of genes associated with specific biological phenotypes is a fundamental step toward understanding the molecular basis underlying development and pathogenesis. Although RNAi-based high-throughput screens are routinely used for this task, false discovery and sensitivity remain a challenge. Here we describe a computational framework for systematic integration of published gene expression data to identify genes defining a phenotype of interest. We applied our approach to rank-order all genes based on their likelihood of determining ES cell (ESC) identity. RNAi-mediated loss-of-function experiments on top-ranked genes unearthed many novel determinants of ESC identity, thus validating the derived gene ranks to serve as a rich and valuable resource for those working to uncover nov

SUBMITTER: Cinghu S 

PROVIDER: S-EPMC4000800 | biostudies-literature | 2014 Apr

REPOSITORIES: biostudies-literature