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PubMed · 15374871

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

Paul Delmar·Stéphane Robin·Jean Jacques Daudin
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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.

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AlgorithmsAnalysis of VarianceComputer SimulationDNA ReplicationGene Expression ProfilingGenetic VariationModels, GeneticModels, StatisticalOligonucleotide Array Sequence AnalysisSoftwareComparative StudyEvaluation StudyJournal ArticleResearch Support, Non-U.S. Gov't

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Paul Delmar, Stéphane Robin, Jean Jacques Daudin. 2004-09-16. VarMixt: efficient variance modelling for the differential analysis of replicated gene expression data.. https://doi.org/10.1093/bioinformatics%2Fbti023

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