This article has not been peer reviewed.
Deposited research articleA non-parametric approach for identifying differentially expressed genes in factorial microarray experiments
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* Corresponding author: Qihua Tan qihua.tan@ouh.fyns-amt.dk
1 Department of Clinical Biochemistry and Genetics, Odense University Hospital, Denmark
2 Department of Statistics, University of Southern Denmark, Denmark
3 Department of Endocrinology, Odense University Hospital, Denmark
Genome Biology 2005, 6:P5 doi:10.1186/gb-2005-6-4-p5
This was the first version of this article to be made available publicly. This article was submitted to Genome Biology for peer review.
The electronic version of this article is the complete one and can be found online at: http://genomebiology.com/2005/6/4/P5
| Received: | 7 March 2005 |
| Published: | 10 March 2005 |
© 2005 BioMed Central Ltd
Abstract
We introduce a non-parametric approach using bootstrap-assisted correspondence analysis to identify and validate genes that are differentially expressed in factorial microarray experiments. Model comparison showed that although both parametric and non-parametric methods capture the different profiles in the data, our method is less inclined to false positive results due to dimension reduction in data analysis.