A multivariate empirical Bayes statistic for replicated microarray time course data

By Y. Tai, Terence P. Speed. 2006

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In this paper we derive a one-sample multivariate empirical Bayes statistic (the MB-statistic) to rank genes in the order of difierential expression from replicated microarray time course experiments . We do this by testing the null hypothesis that the expectation of a k-vector of a gene's expression levels is a multiple of 1k, the vector of k 1s. The importance of moderation in this context is explained. Together with the MB-statistic we have the one-sample e T 2 statistic, a variant of the one-sample Hotelling T 2 . Both the MB-statistic and e T 2 statistic can be used to rank genes in the order of evidence of nonconstancy, incorporating any correlation structure among time point samples and the replication. In a simulation study we show that the one-sample MB-statistic, e T 2 statistic, and moderated Hotelling T 2 statistic achieve the smallest number of false positives and false negatives, and all perform equally well. Several special and limiting cases of the MB-statistic are derived, and two-sample versions are described.

Subfields: Genetics, Molecular Biology, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/d260361576ae4167d4d6f0dd3e8f8b0923d7598c

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Citations in the corpus

The Bayes oracle and asymptotic optimality of multiple testing procedures under sparsity (2010, background): “, see [6, 17–19] and [44]) and full Bayes tests (see, e.”
Using MetaboAnalyst 4.0 for Comprehensive and Integrative Metabolomics Data Analysis (2019, methodology): “These advanced methods include such techniques as multi-way ANOVA, ANOVA-simultaneous component analysis (ASCA; Smilde et al., 2005) and multivariate empirical Bayes time-series analysis (MEBA; Tai & Speed, 2006).”
Using MetaboAnalyst 3.0 for Comprehensive Metabolomics Data Analysis (2016, methodology): “These advanced methods include such techniques as multi-way ANOVA, ANOVA-simultaneous component analysis (ASCA; Smilde et al., 2005), and multivariate empirical Bayes time-series analysis (MEBA) (Tai and Speed, 2006).”
Group SCAD regression analysis for microarray time course gene expression data (2007, unknown): “…of such microarray time course (MTC) gene expression data has focused on two areas: clustering of MTC expression data (Luan and Li, 2003; Ma et al., 2006) and identifying genes that are temporally differentially expressed (Hong and Li, 2006; Tai and Speed, 2006; Yuan and Kendziorski, 2006).”