The percentage of highly significant SNPs is noticeably larger in the hard call analysis than in the soft call analysis. This is because the soft call imputations better account for uncertainty in the imputed values. We recommend using soft calls, or another technique that accounts for imputation uncertainty, in order to reduce false positives. It is worth considering whether we could somehow alter the imputation methods themselves to avoid these false positives altogether; however, it is unclear to what extent this is possible. Imputation algorithms are limited by the information they are provided. For some platforms, the genotyped SNPs provide enough information to accurately infer an unobserved SNP; for other platforms, they do not, regardless of the imputation algorithm. Moreover, current imputation methods have good accuracy, particularly for SNPs with higher imputation R2 (Li et al. 2010), yet even SNPs with high R2 appear among our false positives. This suggests that even well-imputed SNPs can be falsely significant when the imputation error is differential.
