In the nsSNP GWA study, we developed and used a clustering method to call genotypes automatically27. As two research and development chips had been used in the study, we analyzed 7,446 nsSNPs (MAF ≥ 0.01) that had been on both chips or introduced on the second chip, as these had been attempted in at least 2,908 case and 2,664 control samples. We excluded 172 HLA nsSNPs from this study. Poor clustering was defined as a cluster quality score <2.8 (ref. 27) or extreme deviation from Hardy-Weinberg equilibrium (χ12 > 16; 165 SNPs dropped)8. GWA study data were analyzed using the R package snpMatrix26, and follow-up analyses used Stata.
