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

Bioinformatics. 2005 Feb 15;21(4):502-8. doi: 10.1093/bioinformatics/bti023. Epub 2004 Sep 16.

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: [email protected]

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

Publication types

  • Comparative Study
  • Evaluation Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Analysis of Variance
  • Computer Simulation
  • DNA Replication / genetics
  • Gene Expression Profiling / methods*
  • Genetic Variation / genetics
  • Models, Genetic*
  • Models, Statistical
  • Oligonucleotide Array Sequence Analysis / methods*
  • Software*