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Bioinformatics Advance Access published online on March 31, 2009
Bioinformatics, doi:10.1093/bioinformatics/btp177
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© The Author (2009). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Network-Based Multiple Locus Linkage Analysis of Expression Traits

Wei Pan

Division of Biostatistics, School of Public Health, University of Minnesota, A460 Mayo Building (MMC 303), Minneapolis, MN 55455-0378, USA

*To whom correspondence should be addressed. Dr. Wei Pan, E-mail: weip{at}biostat.umn.edu


  Abstract

Motivation: We consider the problem of multiple locus linkage analysis for expression traits of genes in a pathway or a network. To capitalize on co-expression of functionally related genes, we propose a penalized regression method that maps multiple eQTLs for all related genes simultaneously while accounting for their shared functions as specified a priori by a gene pathway or network.

Results: An analysis of a mouse dataset and simulation studies clearly demonstrate the advantage of the proposed method over a standard approach that ignores biological knowledge of gene networks.

Contact: weip{at}biostat.umn.edu

Associate Editor: Dr. Jonathan Wren

Received on November 16, 2008; revised on March 24, 2009; accepted on March 26, 2009

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