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Bioinformatics Advance Access originally published online on October 10, 2006
Bioinformatics 2006 22(23):2905-2909; doi:10.1093/bioinformatics/btl501
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© The Author 2006. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Robust method for detecting differential gene expression in twin studies

Alexander Begun

Institute of Medical Informatics and Statistics, Kiel University Brunswiker Strasse 10, D-24105 Kiel, Germany

Motivation: A steadily increasing number of experiments with microarrays stimulate the further development of the statistical methods of the analysis of gene expression data. One of the central problems in this area is detecting differential gene expression under two or more conditions. Unfortunately, up to now it has not been studied how the correlations between related individuals, such as twins influence the estimates of differential gene expression.

Results: In this paper, we discuss this problem and propose a new method that is robust with respect to correlations of gene expression data for twins.

Contact: a.begun{at}ikmb.uni-kiel.de

Received on June 26, 2006; revised on September 11, 2006; accepted on September 30, 2006

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