SHAVE: shrinkage estimator measured for multiple visits increases power in GWAS of quantitative traits.

ABSTRACT: Measurement error and biological variability generate distortions in quantitative phenotypic data. In longitudinal studies with repeated measurements, the multiple measurements provide a route to reduce noise and correspondingly increase the strength of signals in genome-wide association studies (GWAS).To optimize noise correction, we have developed Shrunken Average (SHAVE), an approach using a Bayesian Shrinkage estimator. This estimator uses regression toward the mean for every individual as a function of (1) their average across visits; (2) their number of visits; and (3) the correlation between visits. Computer simulations support an increase in power, with results very similar to those expected by the assumptions of the model. The method was applied to a real data set for 14 anthropom

SUBMITTER: Meirelles OD 

PROVIDER: S-EPMC3658185 | biostudies-literature | 2013 Jun

REPOSITORIES: biostudies-literature