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Detecting case–control expression quantitative trait loci using locally most powerful or maximin robust rank tests
Author(s) -
Yuan Ao,
Xu Jinfeng,
Yue Qingqi,
Zheng Gang
Publication year - 2011
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.4461
Subject(s) - minimax , rank (graph theory) , statistic , computer science , expression (computer science) , test statistic , statistical hypothesis testing , robustness (evolution) , trait , statistics , data mining , mathematics , mathematical optimization , biology , gene , genetics , combinatorics , programming language
In testing genome‐wide gene expression quantitative trait loci, efficiency robust statistical methods and their computational convenience are most relevant. For this purpose, we propose to use a modified locally most powerful rank test for the analysis of case–control expression data. This modified rank test statistic is computationally simple, robust for non‐normally distributed expression data, and asymptotically locally most powerful. It depends on the specification of a location distribution form for data but is not sensitive to misspecifications. When such a location distribution form cannot be specified, we apply Gastwirth's maximin efficiency robust rank test to gene expression data to maximize the worst Pitman asymptotic relative efficiency among a family of location distributions. We conduct simulation studies to assess their performance and use an application to real data for illustration. Copyright © 2011 John Wiley & Sons, Ltd.