Multiple hypothesis testing and clustering with mixtures of non-central \(t\)-distributions applied in microarray data analysis

DOI10.1016/j.csda.2011.11.016zbMath1242.62079OpenAlexW1966303870MaRDI QIDQ434973

J. Miguel Marín, Maria Teresa Rodríguez-Bernal

Publication date: 16 July 2012

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2011.11.016

zbMATH Keywords

multiple hypothesis testingMCMC computationmicroarray analysismixture distributionsnon-central \(t\)-distribution

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Biochemistry, molecular biology (92C40) Numerical analysis or methods applied to Markov chains (65C40) Paired and multiple comparisons; multiple testing (62J15)

Related Items (2)

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Uses Software

• Bioconductor
• JAGS
• MADE4

Cites Work

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• Multiple hypothesis testing in microarray experiments.
• Simultaneous inference for multiple testing and clustering via a Dirichlet process mixture model
• A Unified Approach for Simultaneous Gene Clustering and Differential Expression Identification
• Multiple Hypothesis Testing by Clustering Treatment Effects
• Detecting differential gene expression with a semiparametric hierarchical mixture method
• Deviance information criteria for missing data models

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