We expect that, in small samples, the use of external recombination rate estimates (as in IMPUTE) might be beneficial, but that with large sample sizes or in the presence of genotyping error our approach, which uses available data to model “recombination” and “mutation” rates should become advantageous. We performed two sets of preliminary comparisons of MaCH and IMPUTE. In the first experiment, we applied IMPUTE [Marchini et al., 2007] to the FUSION GWAS data for chromosome 14 and estimated genotypes for 521 previously genotyped markers [Willer et al., 2006]. Genotypes estimated by IMPUTE and MaCH were identical in 99.2% of cases. In the cases where the two estimates differed, IMPUTE matched experimental genotypes 44.6% of the time, MaCH matched experimental genotypes 52.3% of the time, and both estimates were wrong 3.06% of the time. For the second experiment, we applied IMPUTE to the HGDP data of Conrad et al. [2006]. Table VIII tabulates the proportion of markers imputed with r2>0.80 in each population using either MaCH or IMPUTE (in each case, we selected the HapMap reference panel that provided the
