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Bioinformatics. 2005 Feb 15;21(4):502-8. Epub 2004 Sep 16.

VarMixt: efficient variance modelling for the differential analysis of replicated gene expression data.

Author information

1
Laboratoire MAS Ecole Centrale Paris, Grande Voie des vignes, 92295 Chatenay Malabry, France. delmar@inapg.inra.fr

Abstract

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@inapg.inra.fr

SUPPLEMENTARY INFORMATION:

http://www.inapg.inra.fr/ens_rech/mathinfo/recherche/mathematique/outil.html.

PMID:
15374871
DOI:
10.1093/bioinformatics/bti023
[Indexed for MEDLINE]

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