We identified a set of autosomal SNPs common to both the Illumina and Affymetrix commercial platforms that can robustly monitor residual population structure in European American populations. One commonly used approach for the correction of PS is to adjust simultaneously for a fixed number of top-ranked principal components (PCs) resulting from a principal component analysis [15], [16]. However, this approach may have an overly negative impact on the power if the cases and controls are equally distributed along the selected PCs, or if the adjustment of certain covariates (such as self identified ethnicity, or recruitment center) already included in the association analyses correctly maps to major axes of genetic heterogeneity. To efficiently identify the relevant PCs and keep their number to a minimum while allowing an effective correction, we have developed a permutation procedure to evaluate their effectiveness on PS correction as additional PCs are taken for adjustment in the association test. Taken together, these developments provide a procedure that should be helpful for both PS evaluation and adjustment in GWAS.
