Evaluation of population stratification adjustment using genome-wide or exonic variants.

ABSTRACT: Population stratification may cause an inflated type-I error and spurious association when assessing the association between genetic variations with an outcome. Many genetic association studies are now using exonic variants, which captures only 1% of the genome, however, population stratification adjustments have not been evaluated in the context of exonic variants. We compare the performance of two established approaches: principal components analysis (PCA) and mixed-effects models and assess the utility of genome-wide (GW) and exonic variants, by simulation and using a data set from the Framingham Heart Study. Our results illustrate that although the PCs and genetic relationship matrices computed by GW and exonic markers are different, the type-I error rate of association tests for commo

SUBMITTER: Chen Y 

PROVIDER: S-EPMC7722041 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature