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Bioinformatics Advance Access published online on October 10, 2006
Bioinformatics, 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
Received June 26, 2006
Revised September 11, 2006
Accepted September 30, 2006

Article

Robust method for detecting differential gene expression in twin studies

Alexander Begun 1 *

1 Institute for Medical Information and Statistics, Kiel University, Brunswiker Str. 10, D-24105 Kiel, Germany

* To whom correspondence should be addressed.
Alexander Begun, E-mail: a.begun{at}ikmb.uni-kiel.de


  Abstract

Motivation: A steadily increasing number of experiments with microarrays stimulates 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.

Associate Editor: Joaquin Dopazo
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