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June 2008 Unsupervised empirical Bayesian multiple testing with external covariates
Egil Ferkingstad, Arnoldo Frigessi, Håvard Rue, Gudmar Thorleifsson, Augustine Kong
Ann. Appl. Stat. 2(2): 714-735 (June 2008). DOI: 10.1214/08-AOAS158

Abstract

In an empirical Bayesian setting, we provide a new multiple testing method, useful when an additional covariate is available, that influences the probability of each null hypothesis being true. We measure the posterior significance of each test conditionally on the covariate and the data, leading to greater power. Using covariate-based prior information in an unsupervised fashion, we produce a list of significant hypotheses which differs in length and order from the list obtained by methods not taking covariate-information into account. Covariate-modulated posterior probabilities of each null hypothesis are estimated using a fast approximate algorithm. The new method is applied to expression quantitative trait loci (eQTL) data.

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Egil Ferkingstad. Arnoldo Frigessi. Håvard Rue. Gudmar Thorleifsson. Augustine Kong. "Unsupervised empirical Bayesian multiple testing with external covariates." Ann. Appl. Stat. 2 (2) 714 - 735, June 2008. https://doi.org/10.1214/08-AOAS158

Information

Published: June 2008
First available in Project Euclid: 3 July 2008

zbMATH: 05591295
MathSciNet: MR2524353
Digital Object Identifier: 10.1214/08-AOAS158

Keywords: Bioinformatics , data integration , Empirical Bayes , False discovery rates , multiple hypothesis testing

Rights: Copyright © 2008 Institute of Mathematical Statistics

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Vol.2 • No. 2 • June 2008
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