Bioinformatics Advance Access originally published online on March 31, 2009
Bioinformatics 2009 25(11):1390-1396; doi:10.1093/bioinformatics/btp177
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Network-based multiple locus linkage analysis of expression traits
Division of Biostatistics, School of Public Health, University of Minnesota, A460 Mayo Building (MMC 303), Minneapolis, MN 55455-0378, USA
| Abstract |
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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 expression quantitative trait loci (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
Supplementary information: Supplementary data are available at Bioinformatics online.
Associate Editor: Jonathan Wren
Received on November 16, 2008; revised on March 24, 2009; accepted on March 26, 2009