Statistical tests for detecting associations with groups of genetic variants: generalization, evaluation, and implementation.

ABSTRACT: With recent advances in sequencing, genotyping arrays, and imputation, GWAS now aim to identify associations with rare and uncommon genetic variants. Here, we describe and evaluate a class of statistics, generalized score statistics (GSS), that can test for an association between a group of genetic variants and a phenotype. GSS are a simple weighted sum of single-variant statistics and their cross-products. We show that the majority of statistics currently used to detect associations with rare variants are equivalent to choosing a specific set of weights within this framework. We then evaluate the power of various weighting schemes as a function of variant characteristics, such as MAF, the proportion associated with the phenotype, and the direction of effect. Ultimately, we find that two c

SUBMITTER: Ferguson J 

PROVIDER: S-EPMC3658182 | biostudies-literature | 2013 Jun

REPOSITORIES: biostudies-literature