When exploring genetic associations, population stratification, or genetic differences between subpopulations, is important to identify and control for so that any significant associations found is not due to ancestry. Previous studies have emphasized the importance of this control, particularly in admixed populations (e.g., African American; Montana & Pritchard, 2004; Sankararaman, Sridhar, Kimmel, & Halperin, 2008). The process through which we created the variables to control for population stratification was multidimensional scaling (MDS), completed in PLINK. This process extracts, from genome wide SNP data, clusters of individuals based on their estimated identity by descent. Subjects are assigned a score on each of these clusters representing their membership in a given population cluster. To reduce the computational intensity, we selected a set of one million SNPs randomly across the genome to test for the presence of stratification using the MDS approach. Although these were not a priori identified ancestry information markers, it has been shown that “randomly” selected SNPs perform equally well (Pritchard & Rosenberg, 1999). The results of the MDS allowed for the use of one factor, which accounted for a majority of the variance in population stratification.
