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Efficient estimation of the number of false positives in high-throughput screening

Journal article
Authors Holger Rootzén
Dmitrii Zholud
Published in Biometrika
Volume 102
Issue 3
Pages 695-704
ISSN 0006-3444
Publication year 2015
Published at Department of Mathematical Sciences, Mathematical Statistics
Pages 695-704
Language en
Keywords Correction of p-values, Extreme value statistics, False discovery rate, High-throughput screening, Multiple testing, Positive false discovery rate, SmartTail
Subject categories Mathematics, Mathematical statistics


This paper develops tail estimation methods to handle false positives in multiple testing problems where testing is done at extreme significance levels and with low degrees of freedom, and where the true null distribution may differ from the theoretical one. We show that the number of false positives, conditional on the total number of positives, has an approximately binomial distribution, and we find estimators of the distribution parameter. We also develop methods for estimation of the true null distribution, as well as techniques to compare it with the theoretical one. Analysis is based on a simple polynomial model for very small p-values. Asymptotics that motivate the model, properties of the estimators, and model-checking tools are provided. The methods are applied to two large genomic studies and an fMRI brain scan experiment.

Page Manager: Webmaster|Last update: 9/11/2012

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