We believe that the inflation in Type I error is due to bias introduced by the differential imputation. The imputation uses individuals in the HapMap as a reference panel, and it seems plausible that estimates in the HapMap, particularly for rare alleles, may diverge from the allele frequencies observed in our population. Thus, if a rare allele has similar frequencies in our cases and controls but is not well covered in the HapMap, the p-value calculated when the SNP is measured in one group and imputed in the other will tend to be smaller than the p-value that would arise if that SNP were measured in both groups. Moreover, among SNPs with low MAF, Moskvina et al. (2006) showed that even modest differential errors in genotype calling can yield an inflation in Type I error. Generalized to our setting, this suggests that even slight differential errors in imputation among SNPs with low MAF would lead to false positive associations. This is borne out by our results, where we see larger numbers of highly significant p-values among SNPs with low MAF, as shown in Figure 1.
