The need for careful QC/QA of genotypic data in GWAS is well recognized and several publications address various aspects [Broman 1999; Chanock, et al. 2007; Wellcome Trust Case Control Consortium 2007; Manolio, et al. 2007; McCarthy, et al. 2008; Miyagawa, et al. 2008; Ziegler, et al. 2008]. We have extended these methods to include some new approaches that (1) combine analysis of allelic probe intensities and called genotypes to distinguish gender misidentification from sex chromosome aberrations, (2) detect autosomal chromosome aberrations that may affect genotype calling accuracy, (3) infer DNA sample quality from relatedness and allelic intensities, (4) use duplicate concordance to infer SNP quality, (5) detect genotyping artifacts from dependence of Hardy-Weinberg equilibrium (HWE) test p-values on allelic frequency, and (6) demonstrate sensitivity of principal components analysis (PCA) to SNP selection. Here we describe the QC/QA process applied to GENEVA studies and provide some guidelines for the design of GWAS to avoid experimental artifacts.
