Unsupervised empirical Bayesian multiple testing with external covariates

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dc.creatorFerkingstad, Egil
dc.creatorFrigessi, Arnoldo
dc.creatorRue, Håvard
dc.creatorThorleifsson, Gudmar
dc.creatorKong, Augustine
dc.date2008-07-29
dc.date.accessioned2026-07-07T09:53:31Z
dc.date.available2026-07-07T09:53:31Z
dc.descriptionIn 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.
dc.descriptionPublished in at http://dx.doi.org/10.1214/08-AOAS158 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org)
dc.identifierhttps://arxiv.org/abs/0807.4658
dc.identifierhttp://arxiv.org/abs/0807.4658
dc.identifierAnnals of Applied Statistics 2008, Vol. 2, No. 2, 714-735
dc.identifierdoi:10.1214/08-AOAS158
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/165982
dc.subjectApplications
dc.titleUnsupervised empirical Bayesian multiple testing with external covariates
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