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  • Deposited research article
  • Open Access

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

  • 1Email author,
  • 1,
  • 2,
  • 3,
  • 3 and
  • 1
Genome Biology20056:P5

https://doi.org/10.1186/gb-2005-6-4-p5

  • Received: 7 March 2005
  • Published:

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.

Keywords

  • Singular Value Decomposition
  • Correspondence Analysis
  • Microarray Experiment
  • Interactive Variable
  • Gene Contribution

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