Local coherence in genetic interaction patterns reveals prevalent functional versatility

Bioinformatics
Shuye PuShoshana J Wodak

Abstract

Epistatic or genetic interactions, representing the effects of mutating one gene on the phenotypes caused by mutations in one or more distinct genes, can be very helpful for uncovering functional relationships between genes. Recently, the epistatic miniarray profiles (E-MAP) method has emerged as a powerful approach for identifying such interactions systematically. For E-MAP data analysis, hierarchical clustering is used to partition genes into groups on the basis of the similarity between their global interaction profiles, and the resulting descriptions assign each gene to only one group, thereby ignoring the multifunctional roles played by most genes. Here, we present the original local coherence detection (LCD) algorithm for identifying groups of functionally related genes from E-MAP data in a manner that allows individual genes to be assigned to more than one functional group. This enables investigation of the pleiotropic nature of gene function. The performance of our algorithm is illustrated by applying it to two E-MAP datasets and an E-MAP-like in silico dataset for the yeast Saccharomyces cerevisiae. In addition to recapitulating the majority of the functional modules and many protein complexes reported previously, our ...Continue Reading

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Sep 19, 2009·Molecular BioSystems·Michal Breker, Maya Schuldiner
Jun 10, 2010·Bioinformatics·Ariel JaimovichNir Friedman
May 10, 2011·Bioinformatics·Jesse Gillis, Paul Pavlidis
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