We confirmed the general applicability of our results to real genotype data, by applying our methods to 538 control samples from a GWA case-control study of Type II diabetes (FUSION). We studied the following two scenarios: (1) all 538 samples and a modest effect (single-marker heritability of 4.3%); and (2) small sample size of 50 individuals and a large effect (single-marker heritability of 59.8%). To examine the phenomenon of seeing greatly increased power for the mixture models at sites with poor imputation accuracy, we report results for small sample size by low imputation accuracy (R2 <0.56) and “high” accuracy (R2 ≥0.56). (Due to the constraints of the real data, there does not exist a full spectrum of allele frequencies for plots by allele frequency. The cutoff of 0.56 was chosen based on a visual examination of Fig. 3.) In all scenarios, the power from using mixture models equals or exceeds those for the dosage and best-guess summaries, although only the scenario of low imputation accuracy and large effects show a pronounced difference. Results are displayed in Table IV.
