Extreme sampling design in genetic association mapping of quantitative trait loci using balanced and unbalanced case-control samples.

ABSTRACT: It is extremely expensive to conduct large sample size array- or sequencing based genome scale association studies. For a quantitative trait, an extreme case-control study design may improve the power and reduce the cost of variant calling. We investigated the performance of extreme study design when various proportions of samples are selected from the tails of phenotype distribution. Using simulations, we show that when risk genotypes become rare in the population and effect size is relatively small, it is beneficial to carry out an extreme sampling study. In particular, the number of selected cases and controls can even be unbalanced such that power is further increased, compared with a balanced selection. Our application to two data sets: methadone dose data and yearling weight data, de

SUBMITTER: Li Y 

PROVIDER: S-EPMC6820758 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature