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Deposited research article

A non-parametric approach for identifying differentially expressed genes in factorial microarray experiments

Qihua Tan¹ , Jesper Dahlgaard¹, Werner Vach², Basem M Abdallah³, Moustapha Kassem³ and Torben A Kruse¹

¹Department of Clinical Biochemistry and Genetics, Odense University Hospital, Denmark

²Department of Statistics, University of Southern Denmark, Denmark

³Department of Endocrinology, Odense University Hospital, Denmark

author email corresponding author email

Genome Biology 2005, 6:P5doi:10.1186/gb-2005-6-4-p5

Published:	10 March 2005

This was the first version of this article to be made available publicly. This article was submitted to Genome Biology for peer review.

Subject areas: Bioinformatics, Methods, Genome studies

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.