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Bioinformatics Advance Access originally published online on February 11, 2009
Bioinformatics 2009 25(8):1019-1025; doi:10.1093/bioinformatics/btp076
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© The Author 2009. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

A flexible two-stage procedure for identifying gene sets that are differentially expressed

Ruth Heller 1,*, Elisabetta Manduchi 2, Gregory R. Grant 2 and Warren J. Ewens 3

1Department of Statistics, Wharton School, University of Pennsylvania, Philadelphia, PA 19104-6340, 2Computational Biology and Informatics Laboratory, Center for Bioinformatics, University of Pennsylvania, Philadelphia, PA 19104-6021 and 3Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA

*To whom correspondence should be addressed.


  Abstract

Motivation: Microarray data analysis has expanded from testing individual genes for differential expression to testing gene sets for differential expression. The tests at the gene set level may focus on multivariate expression changes or on the differential expression of at least one gene in the gene set. These tests may be powerful at detecting subtle changes in expression, but findings at the gene set level need to be examined further to understand whether they are informative and if so how.

Results: We propose to first test for differential expression at the gene set level but then proceed to test for differential expression of individual genes within discovered gene sets. We introduce the overall false discovery rate (OFDR) as an appropriate error rate to control when testing multiple gene sets and genes. We illustrate the advantage of this procedure over procedures that only test gene sets or individual genes.

Availability: R code (www.r-project.org) for implementing our approach is included as supplementary material.

Contact: ruheller{at}whatron.upenn.edu

Associate Editor: Joaquin Dopazo

Received on August 4, 2008; revised on January 28, 2009; accepted on February 3, 2009

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