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Open Access

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

  • Qihua Tan1Email author,
  • Jesper Dahlgaard1,
  • Werner Vach2,
  • Basem M Abdallah3,
  • Moustapha Kassem3 and
  • Torben A Kruse1
Genome Biology20056:P5

Received: 7 March 2005

Published: 10 March 2005


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.