The mixture-model-based procedures were considerably more computationally demanding, based on our implementations in the R software package. Per-marker run times for the mixture-models averaged approximately 4 sec for 1-df (about 300 times longer than for the best-guess and dosage methods) and 20 sec for 2-df regression models. However, calculations for methods applied in this study can be conducted in parallel. We estimate that an application of mixture models to poorly imputed SNPs in a GWA study could be completed in a couple of days using tens of CPUs.
