Laplace Approximated EM Microarray Analysis: An Empirical Bayes Approach for Comparative Microarray Experiments

Laplace Approximated EM Microarray Analysis: An Empirical Bayes Approach for Comparative Microarray Experiments

A two-groups mixed-effects model for the comparison of (normalized) microarray data from two treatment groups is considered. Most competing parametric methods that have appeared in the literature are obtained as special cases or by minor modification of the proposed model. Approximate maximum likelihood fitting is accomplished via a fast and scalable algorithm, which we call LEMMA (Laplace appr...

Empirical Bayes Analysis of a Microarray Experiment

Microarrays are a novel technology that facilitates the simultaneous measurement of thousands of gene expression levels. A typical microarray experiment can produce millions of data points, raising serious problems of data reduction, and simultaneous inference. We consider one such experiment in which oligonucleotide arrays were employed to assess the genetic effects of ionizing radiation on se...

Parametric Empirical Bayes Methods for Microarray Data

Design and Analysis of Comparative Microarray Experiments

This chapter discusses the design and analysis of relatively simple comparative experiments involving microarrays. Some of the discussion applies to all the most widely used kinds of microarrays, that is, radiolabelled cDNA arrays on nylon membranes, two-color, fluorescently labeled cDNA or long oligonucleotide arrays on glass slides, or single color, fluorescently labeled, high-density short o...

An empirical Bayes' approach to joint analysis of multiple microarray gene expression studies.

With the prevalence of gene expression studies and the relatively low reproducibility caused by insufficient sample sizes, it is natural to consider joint analysis that could combine data from different experiments effectively to achieve improved accuracy. We present in this article a model-based approach for better identification of differentially expressed genes by incorporating data from dif...