NDLI: Evaluating FDR and stratified FDR control approaches for high-throughput biological studies

Content Provider	IEEE Xplore Digital Library
Author	Jinfeng Zou Guini Hong Junjie Zheng Chunxiang Hao Jing Wang Zheng Guo
Copyright Year	2012
Description	Author affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150086 (Zheng Guo) \|\| College of Life Science, University of Electronic Science and Technology of China, Chengdu 610054 (Jinfeng Zou; Guini Hong; Junjie Zheng; Chunxiang Hao; Jing Wang)
Abstract	False discovery rate (FDR) control procedures are commonly used for the correction of multiple testing in high-throughput biological studies. Although the expectation of FDR estimations can be controlled, the variance of the FDR estimations has not been fully analysed. Especially, the effect of the variance of the FDR estimator on the stratified FDR control approach, which is proposed to improve the statistical powers of FDR control procedures, is unclear. In this study, we analyzed the effects of three major factors (the percentage of true null hypotheses, the number of hypotheses and the effect size of true alternative hypotheses) on the performances of the FDR and stratified FDR control approaches. We show that the variance of the FDR estimations tends to be small when at least one of the following conditions is satisfied: (1) the percentage of true null hypotheses is not too large, (2) the number of tests is relatively large, or (3) the effect size of true alternative hypotheses is not too small. We demonstrated that when all the hypotheses are stratified into two groups, the variance of the stratified FDR estimations tends to be small if each group satisfies at least one of the above mentioned conditions. In such a situation, the actual stratified FDR for an experiment tends to be under the given control level.
Starting Page	684
Ending Page	686
File Size	103877
Page Count	3
File Format	PDF
ISBN	9781467322058
e-ISBN	9781467322072
DOI	10.1109/ISRA.2012.6219282
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-06-03
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Simulation Estimation Educational institutions Diabetes Bioinformatics False discovery rate (FDR) Stratified FDR control Statistical power Standards Robots Testing
Content Type	Text
Resource Type	Article

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