Bioinformatics Advance Access originally published online on July 29, 2004
Bioinformatics 2004 20(18):3553-3564; doi:10.1093/bioinformatics/bth442
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Bioinformatics vol. 20 issue 18 © Oxford University Press 2004; all rights reserved.
The Baumgartner-Weiß-Schindler test for the detection of differentially expressed genes in replicated microarray experiments
1 Institute for Medical Informatics, Biometry and Epidemiology, University of Duisburg-Essen, Hufelandstr. 55, D-45122 Essen, Germany and 2 Department of Mathematics and Statistics, University of Otago, P.O. Box 56, Dunedin, New Zealand
Received on December 23, 2003; revised on June 30, 2004; accepted on July 26, 2004
Advance Access Publication July 29, 2004
Motivation: An important application of microarray experiments is to identify differentially expressed genes. Because microarray data are often not distributed according to a normal distribution nonparametric methods were suggested for their statistical analysis. Here, the Baumgartner-Weiß-Schindler test, a novel and powerful test based on ranks, is investigated and compared with the parametric t-test as well as with two other nonparametric tests (Wilcoxon rank sum test, Fisher-Pitman permutation test) recently recommended for the analysis of gene expression data.
Results: Simulation studies show that an exact permutation test based on the Baumgartner-Weiß-Schindler statistic B is preferable to the other three tests. It is less conservative than the Wilcoxon test and more powerful, in particular in case of asymmetric or heavily tailed distributions. When the underlying distribution is symmetric the differences in power between the tests are relatively small. Thus, the Baumgartner-Weiß-Schindler is recommended for the usual situation that the underlying distribution is a priori unknown.
Availability: SAS code available on request from the authors.
Contact: markus.neuhaeuser{at}medizin.uni-essen.de
* To whom correspondence should be addressed.
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