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Bioinformatics Advance Access originally published online on August 18, 2009
Bioinformatics 2009 25(21):2780-2786; doi:10.1093/bioinformatics/btp502
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© The Author(s) 2009. Published by Oxford University Press.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Statistical methods for gene set co-expression analysis

YounJeong Choi 1 and Christina Kendziorski 2,*

1 Department of Statistics and2 Department of Biostatistics and Medical Informatics, University of Wisconsin - Madison 1300 University Avenue, Madison, WI 53706, USA

* To whom correspondence should be addressed.


  Abstract

Motivation: The power of a microarray experiment derives from the identification of genes differentially regulated across biological conditions. To date, differential regulation is most often taken to mean differential expression, and a number of useful methods for identifying differentially expressed (DE) genes or gene sets are available. However, such methods are not able to identify many relevant classes of differentially regulated genes. One important example concerns differentially co-expressed (DC) genes.

Results: We propose an approach, gene set co-expression analysis (GSCA), to identify DC gene sets. The GSCA approach provides a false discovery rate controlled list of interesting gene sets, does not require that genes be highly correlated in at least one biological condition and is readily applied to data from individual or multiple experiments, as we demonstrate using data from studies of lung cancer and diabetes.

Availability: The GSCA approach is implemented in R and available at www.biostat.wisc.edu/~kendzior/GSCA/.

Contact: kendzior{at}biostat.wisc.edu

Supplementary information: Supplementary data are available at Bioinformatics online.

Associate Editor: Martin Bishop

Received on April 2, 2009; revised on July 20, 2009; accepted on August 4, 2009

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