A multivariate empirical Bayes statistic for replicated microarray time course data

A Multivariate Empirical Bayes Statistic for Replicated Microarray Time Course Data

In this paper we derive a one-sample multivariate empirical Bayes statistic (the MB-statistic) to rank genes in the order of differential 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...

On the gene ranking of replicated microarray time course data

Consider the gene ranking problem of replicated microarray time course experiments where there are multiple biological conditions, and genes of interest are those whose temporal profiles are different across conditions. We derive the multi-sample multivariate empirical Bayes statistic for ranking genes in the order of differential expression, from both longitudinal and cross-sectional replicate...

Parametric Empirical Bayes Methods for Microarray Data

Reduced-rank Multivariate Model for Time-course Microarray Data

In this paper we present a novel, multi-gene approach to time course microarray experiments. One of the advantages of our approach is an explicit modeling of correlation structure among gene expression data. The approach proposed is computationally attractive. We apply the model to the well-known cell-cycle yeast microarray data and present results that compare favorably to the results of the p...

Materials for On the gene ranking of replicated microarray time course data

In contrast, when ν → 0, the posterior odds are just equation (5) with ν replaced by 0. This means that gene-specific Ws are so different such that moderation is not able to move these gene-specific W at all. Thus, the degree of moderation reflects how similar these gene-specific within group sums of squares are. The more similar they are, the greater degree of moderation our proposed statistic...