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Laplace approximated EM Microarray Analysis: an empirical Bayes approach for
 

Summary: Laplace approximated EM Microarray
Analysis: an empirical Bayes approach for
comparative microarray experiments
Haim Bar
, James Booth
, Elizabeth Schifano
, Martin T. Wells
March 2010
Abstract
A two groups mixed-effects model for the comparison of (normal-
ized) 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 pro-
posed model. Approximate maximum likelihood fitting is accom-
plished via a fast and scalable algorithm, which we call LEMMA
(Laplace approximated EM Microarray Analysis). The posterior odds
of treatment×gene interactions, derived from the model, involve shrink-
age estimates of both the interactions and of the gene specific error
variances. Genes are classified as being associated with treatment
based on the posterior odds and the local false discovery rate (fdr)

  

Source: Angenent, Lars T. - Department of Biological and Environmental Engineering, Cornell University

 

Collections: Renewable Energy; Engineering