Background Genome-wide association (GWA) studies that use population-based
association approaches may identify spurious associations in the presence of population
admixture. In this paper, we propose a novel three-stage approach that is computationally
efficient and robust to population admixture and more powerful than the family-based
association test (FBAT) for GWA studies with family data. We propose a three-stage
approach for GWA studies with family data. The first stage is to perform linear regression …

GWAF, Genome-Wide Association analyses with Family, is an R package designed for
GWAF. It implements association tests between a batch of genotyped or imputed single
nucleotide polymorphisms (SNPs) and a binary or continuous trait with user specified
genetic model, and generates informative results from the analyses. In addition, GWAF
provides functions to visualize results. We evaluated GWAF using a simulated continuous
trait and a binary trait dichotomized from the simulated continuous trait with real genotype …