Comparison of genome-wide association methods in analyses of admixed populations with complex familial relationships.

ABSTRACT: Population structure is known to cause false-positive detection in association studies. We compared the power, precision, and type-I error rates of various association models in analyses of a simulated dataset with structure at the population (admixture from two populations; P) and family (K) levels. We also compared type-I error rates among models in analyses of publicly available human and dog datasets. The models corrected for none, one, or both structure levels. Correction for K was performed with linear mixed models incorporating familial relationships estimated from pedigrees or genetic markers. Linear models that ignored K were also tested. Correction for P was performed using principal component or structured association analysis. In analyses of simulated and real data, linear mixe

SUBMITTER: Kadri NK 

PROVIDER: S-EPMC3963841 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature