(total dataset including EA subjects who were not included in the linkage analysis) had ≤1% missing data, and 30 subjects had 1–5% missing data. No subject had >5% missing data. By marker, 5573 markers had <1% missing data; 40 had 1–2% missing; 9 had 2–3% missing; 5 had 3–4% missing; 2 had 4–5% missing; 2 had 5–6% missing; and 2 had 6–8% missing. No marker had >8% missing data. Linkage analyses were performed using the package Merlin (32). To address the issue of marker-marker linkage disequilibrium (LD) in the data set that has the potential to spuriously inflate linkage results, SNPs showing LD were grouped into clusters (33). Clusters were created when the pairwise r2 between neighboring SNPs was greater than 0.10. Analyses were repeated with r2 thresholds of 0.05, 0.2, and 0.3 to gauge the effect of LD on the linkage results. Map positions for the clusters were calculated as the midpoint between the positions of the outer-most SNPs in the cluster. In the few instances of an obligate recombination among SNPs in a cluster, genotypes for SNPs in the cluster were recoded as missing for the recombinant individuals. Population haplotype frequencies were calculated using the available genotype data
