Quantile–quantile (Q–Q) plots in Figure 3 illustrate the GWAS results using different study designs as described in Table 1. The test statistics in all Q–Q plots were corrected by their genomic control inflation factor λGC.16 First we used combined data of ASPs (imputed Sib 1 and genotyped Sib 2) and genotyped controls. Results (Figure 3a) show deviation from first diagonal (dashed line), hence, inflation of test statistics (λGC=1.16). Next (Figure 3b), we compared genotyped Sib 2 and controls (Illumina660 for cases and Illumina550 for controls, respectively): λGC=1.03. One might conjecture that inflated test statistics in Figure 3a were caused by also considering imputed sibling data. We then investigated whether this inflation is an artifact solely from imputation, or due to combining different arrays. To determine the possibility of a chip (or batch) effect, we conducted ASP and control analysis only on genotyped overlapping 60K SNPs with Affy500 (Sib 1), Illumina660 (Sib 2), and Illumina550 (control). In Figure 3c, the genomic control inflation factor is decreased from 1.16 to 1.06 as compared with Figure 3a and increased from 1.03 to 1.06
