In summary, we have described and evaluated a very effective model for haplotyping and genotype imputation in whole genome studies. The idea of genotype imputation is not new and was outlined as early as 2006 [Scheet and Stephens, 2006]. Here, we evaluate the practical performance of imputation based on a variety of genotyping platforms and populations, using both simulations and real data. We show that our model leads to imputed genotypes whose quality improves as more data becomes available, either because a larger reference panel is used or because study samples are genotyped in finer detail. Similarly, haplotype estimates improve in quality as more individuals are genotyped. Furthermore, we have introduced novel approaches for the analysis of short read shotgun sequencing data, which is likely to become extremely important as human geneticists move beyond chip-based genotyping to resequencing (as in the 1,000 Genomes Project, whose initial design was partly based on the simulations summarized in our Table VI, see http://www.1000genomes.org for more details).
