One principle of classical epidemiologic study design is that the distribution of risk factors of interest in controls should be the same as the distribution in the population from which cases have been ascertained [13]. A population-based study satisfies this principle by choosing a random sample of controls from the same population from which cases are selected. Violation of this principle in the studies of genetic effects may be of less concern than in the studies of environmental risk factors, if the distribution of population ancestry in individual cases and controls is available and can be used to control the type I error rate at the cost of only a modest drop in power. Principal component analysis [14]–[17] or other methods [18], [19] can be used to estimate the population ancestry from the genotypes on a panel of SNPs not associated with the disease status. The SNP panel can be selected from the large number of SNPs typed in GWAS, of which the vast majority (>99%) are not expected to be related to the disease under study. Furthermore, a second
