A strategy for extracting and analyzing large-scale quantitative epistatic interaction data

Sean R. Collins, Maya Schuldiner, Nevan J. Krogan, Jonathan S. Weissman

Research output: Contribution to journalArticle

223 Scopus citations

Abstract

Recently, approaches have been developed for high-throughput identification of synthetic sick/lethal gene pairs. However, these are only a specific example of the broader phenomenon of epistasis, wherein the presence of one mutation modulates the phenotype of another. We present analysis techniques for generating high-confidence quantitative epistasis scores from measurements made using synthetic genetic array and epistatic miniarray profile (E-MAP) technology, as well as several tools for higher-level analysis of the resulting data that are greatly enhanced by the quantitative score and detection of alleviating interactions.

Original languageEnglish (US)
Article numberR63
JournalGenome Biology
Volume7
Issue number7
DOIs
StatePublished - Jul 21 2006

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Genetics
  • Cell Biology

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