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Empirical Bayes Analysis of a Microarray Experiment (2001)
| Venue: | Journal of the American Statistical Association |
| Citations: | 491 - 20 self |
BibTeX
@ARTICLE{Efron01empiricalbayes,
author = {Bradley Efron and Robert Tibshirani and John D. Storey and Virginia Tusher},
title = {Empirical Bayes Analysis of a Microarray Experiment},
journal = {Journal of the American Statistical Association},
year = {2001},
pages = {1151--1160}
}
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Abstract
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 seven thousand human genes. A simple nonparametric empirical Bayes model is introduced, which is used to guide the ef � cient reduction of the data to a single summary statistic per gene, and also to make simultaneous inferences concerning which genes were affected by the radiation. Although our focus is on one speci � c experiment, the proposed methods can be applied quite generally. The empirical Bayes inferences are closely related to the frequentist false discovery rate (FDR) criterion. 1.
Keyphrases
empirical bayes analysis microarray experiment simultaneous inference empirical bayes inference data point single summary statistic frequentist false discovery rate typical microarray experiment speci experiment serious problem ef cient reduction simple nonparametric empirical bayes model data reduction human gene novel technology simultaneous measurement genetic effect gene expression level
