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Gene‐based genetic association test with adaptive optimal weights
Author(s) -
Chen Zhongxue,
Lu Yan,
Lin Tong,
Liu Qingzhong,
Wang Kai
Publication year - 2018
Publication title -
genetic epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.301
H-Index - 98
eISSN - 1098-2272
pISSN - 0741-0395
DOI - 10.1002/gepi.22098
Subject(s) - association test , association (psychology) , kernel (algebra) , genetic association , set (abstract data type) , computer science , power (physics) , genetics , gene , biology , computational biology , mathematics , genotype , single nucleotide polymorphism , psychology , physics , combinatorics , quantum mechanics , programming language , psychotherapist
It is well known that using proper weights for genetic variants is crucial in enhancing the power of gene‐ or pathway‐based association tests. To increase the power, we propose a general approach that adaptively selects weights among a class of weight families and apply it to the popular sequencing kernel association test. Through comprehensive simulation studies, we demonstrate that the proposed method can substantially increase power under some conditions. Applications to real data are also presented. This general approach can be extended to all current set‐based rare variant association tests whose performances depend on variant's weight assignment.