A modified false discovery rate multiple-comparisons procedure for discrete data, applied to human immunodeficiency virus genetics
Author: Peter B. Gilbert1
Source: Journal of the Royal Statistical Society: Series C (Applied Statistics), Volume 54, Number 1, January 2005 , pp. 143-158(16)
Publisher: Blackwell Publishing
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Abstract:
Summary. To help to design vaccines for acquired immune deficiency syndrome that protect broadly against many genetic variants of the human immunodeficiency virus, the mutation rates at 118 positions in HIV amino-acid sequences of subtype C versus those of subtype B were compared. The false discovery rate (FDR) multiple-comparisons procedure can be used to determine statistical significance. When the test statistics have discrete distributions, the FDR procedure can be made more powerful by a simple modification. The paper develops a modified FDR procedure for discrete data and applies it to the human immunodeficiency virus data. The new procedure detects 15 positions with significantly different mutation rates compared with 11 that are detected by the original FDR method. Simulations delineate conditions under which the modified FDR procedure confers large gains in power over the original technique. In general FDR adjustment methods can be improved for discrete data by incorporating the modification proposed.Keywords: Bonferroni; False discovery rate; Genetics data; High dimensional data; Human immunodeficiency virus vaccine trial; Hypothesis testing; Simultaneous inference
Document Type: Research article
DOI: 10.1111/j.1467-9876.2005.00475.x
Affiliations: 1: Fred Hutchinson Cancer Research Center and University of Washington, Seattle, USA
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