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 set of SNPs, minimally correlated with the previous one chosen for ancestry inference can be used to evaluate the extent of confounding by PS as well as the effectiveness of the correction for PS, by comparing the distribution of the test statistic (with or without the correction for PS) observed over the second set of SNPs with its expected distribution under the null hypothesis. Systematic inflation in the observed statistics would indicate that ancestry effects have not been fully controlled. Thus, we postulate that the analysis of thousands of well-chosen SNPs distributed throughout the genome could permit relaxation of the requirement that cases and controls share the same population of origin. In this regard, it is possible to analyze cases and controls recruited from independently designed studies or allow the use of a single, common control group for a variety of disease groups, a strategy successfully used by the Welcome Trust Case Control Consortium (WTCCC) to identify novel variants in
