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Bioinformatics Advance Access originally published online on August 20, 2008
Bioinformatics 2008 24(20):2376-2383; doi:10.1093/bioinformatics/btn440
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© The Author 2008. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Local coherence in genetic interaction patterns reveals prevalent functional versatility

Shuye Pu 1,*, Karen Ronen 1, James Vlasblom 1, Jack Greenblatt 2,3 and Shoshana J. Wodak 1,3,4

1Molecular Structure and Function Program, Hospital for Sick Children, 555 University Avenue, Toronto, ON, Canada M5G 1X8, 2Terrence Donnelly Centre for Cellular & Biomolecular Research, 160 College Street, Toronto, ON, Canada M5S 3E1, 3Department of Molecular Genetics and 4Department of Biochemistry, University of Toronto, 1 King's College Circle, Toronto, ON, Canada M5S 1A8

*To whom correspondence should be addressed.


  Abstract

Motivation: Epistatic or genetic interactions, representing the effects of mutating one gene on the phenotypes caused by mutations in one or moredistinct 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.

Results: 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 algorithm uncovers many recently documented and novel multifunctional relationships between genes and gene groups. Our algorithm hence represents a valuable tool for uncovering new roles for genes with annotated functions and for mapping groups of genes and proteins into pathways.

Availability: A Java implementation of the LCD algorithm is available at URL http://genepro.ccb.sickkids.ca/biclustering.html

Contact: shuyepu{at}sickkids.ca

Supplementary information: Supplementary data are available at Bioinformatics online.

Associate Editor: Trey Ideker

Received on May 13, 2008; revised on August 1, 2008; accepted on August 15, 2008

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