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Title: A novel gene-set association test based on variance-gamma distribution.

Authors: Chen, Zhongxue; Liu, Qingzhong; Wang, Kai

Published In Stat Methods Med Res, (2019 09)

Abstract: Several gene- or set-based association tests have been proposed recently in the literature. Powerful statistical approaches are still highly desirable in this area. In this paper we propose a novel statistical association test, which uses information of the burden component and its complement from the genotypes. This new test statistic has a simple null distribution, which is a special and simplified variance-gamma distribution, and its p-value can be easily calculated. Through a comprehensive simulation study, we show that the new test can control type I error rate and has superior detecting power compared with some popular existing methods. We also apply the new approach to a real data set; the results demonstrate that this test is promising.

PubMed ID: 30056781 Exiting the NIEHS site

MeSH Terms: Computer Simulation; Genetic Association Studies/methods*; Genetic Association Studies/statistics & numerical data*; Genotype; Humans; Models, Genetic*; Models, Statistical*; Phenotype; Polymorphism, Single Nucleotide

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