False discovery rate control in two-stage designs
نویسندگان
چکیده
منابع مشابه
Optimal two-stage genome-wide association designs based on false discovery rate
Genome-wide association studies are likely to be conducted in large scale in the near future. In such studies, searching over hundreds of thousands of markers for the few ones that are associated with disease brings out the multiple-hypothesis testing problem in its severe form. We explore, in a two-stage design, how the use of false discovery rate (FDR) can alleviate the burden of a prohibitiv...
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We provide the first differentially private algorithms for controlling the false discovery rate (FDR) in multiple hypothesis testing, with essentially no loss in power under certain conditions. Our general approach is to adapt a well-known variant of the Benjamini-Hochberg procedure (BHq), making each step differentially private. This destroys the classical proof of FDR control. To prove FDR co...
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Multiple hypotheses testing is a core problem in statistical inference and arises in almost every scientific field. Given a sequence of null hypotheses H(n) = (H1, . . . ,Hn), Benjamini and Hochberg [BH95] introduced the false discovery rate (FDR), which is the expected proportion of false positives among rejected null hypotheses, and proposed a testing procedure that controls FDR below a pre-a...
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In the context of large-scale multiple hypothesis testing, the hypotheses often possess certain group structures based on additional information such as Gene Ontology in gene expression data and phenotypes in genome-wide association studies. It is hence desirable to incorporate such information when dealing with multiplicity problems to increase statistical power. In this article, we demonstrat...
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This research is motivated from the analysis of a real gene expression data that aims to identify a subset of "interesting" or "significant" genes for further studies. When we blindly applied the standard false discovery rate (FDR) methods, our biology collaborators were suspicious or confused, as the selected list of significant genes was highly unbalanced: there were ten times more under-expr...
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ژورنال
عنوان ژورنال: BMC Bioinformatics
سال: 2012
ISSN: 1471-2105
DOI: 10.1186/1471-2105-13-81