Test selection with application to detecting disease association with multiple SNPs.

ABSTRACT: We consider the motivating problem of testing for association between a phenotype and multiple single nucleotide polymorphisms (SNPs) within a candidate gene or region. Various statistical approaches have been proposed, including those based on either (combining univariate) single-locus analyses or (multivariate) multilocus analyses. However, it is known in theory that there is no single uniformly most powerful test to detect association with multiple SNPs. On the other hand, several tests have been shown to be among frequent winners across a range of practical situations, but the identity of the most powerful one changes with the situation in an unknown way. Here we propose a novel test selection procedure to select from five such tests: a so-called UminP test that combines multiple univa

SUBMITTER: Pan W 

PROVIDER: S-EPMC3725887 | biostudies-literature | 2010

REPOSITORIES: biostudies-literature