Bioinformatics Advance Access originally published online on September 16, 2004
Bioinformatics 2005 21(4):502-508; doi:10.1093/bioinformatics/bti023
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Bioinformatics vol. 21 issue 4 © Oxford University Press 2005; all rights reserved.
VarMixt: efficient variance modelling for the differential analysis of replicated gene expression data
1 Laboratoire MAS Ecole Centrale Paris, Grande Voie des vignes, 92295 Chatenay Malabry, France
2 UMR ENGREF/INAPG/INRA 518, INAPG 16, rue Claude Bernard, 75005 Paris, France
*To whom correspondence should be addressed.
Motivation: Identifying differentially regulated genes in experiments comparing two experimental conditions is often a key step in the microarray data analysis process. Many different approaches and methodological developments have been put forward, yet the question remains open.
Results: Varmixt is a powerful and efficient novel methodology for this task. It is based on a flexible and realistic variance modelling strategy. It compares favourably with other popular techniques (standard t-test, SAM and Cyber-T). The relevance of the approach is demonstrated with real-world and simulated datasets. The analysis strategy was successfully applied to both a ‘two-colour’ cDNA microarray and an Affymetrix Genechip. Strong control of false positive and false negative rates is proven in large simulation studies.
Availability: The R package is freely available at http://www.inapg.inra.fr/ens_rech/mathinfo/recherche/mathematique/outil.html
Contact: delmar{at}inapg.inra.fr
Supplementary information: http://www.inapg.inra.fr/ens_rech/mathinfo/recherche/mathematique/outil.html
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