Literature DB >> 15374871

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

Paul Delmar1, Stéphane Robin, Jean Jacques Daudin.   

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.

Mesh:

Year:  2004        PMID: 15374871     DOI: 10.1093/bioinformatics/bti023

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  34 in total

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2.  Endometrium as an early sensor of in vitro embryo manipulation technologies.

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3.  Synergistic contribution of the Legionella pneumophila lqs genes to pathogen-host interactions.

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4.  Control of flagellar gene regulation in Legionella pneumophila and its relation to growth phase.

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5.  New insights into sulfur metabolism in yeasts as revealed by studies of Yarrowia lipolytica.

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Journal:  BMC Microbiol       Date:  2010-02-18       Impact factor: 3.605

9.  Should we abandon the t-test in the analysis of gene expression microarray data: a comparison of variance modeling strategies.

Authors:  Marine Jeanmougin; Aurelien de Reynies; Laetitia Marisa; Caroline Paccard; Gregory Nuel; Mickael Guedj
Journal:  PLoS One       Date:  2010-09-03       Impact factor: 3.240

10.  Gene expression profiling to identify eggshell proteins involved in physical defense of the chicken egg.

Authors:  Vincent Jonchère; Sophie Réhault-Godbert; Christelle Hennequet-Antier; Cédric Cabau; Vonick Sibut; Larry A Cogburn; Yves Nys; Joel Gautron
Journal:  BMC Genomics       Date:  2010-01-21       Impact factor: 3.969

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