Several important points emerge from this description. First, the accuracy with which the study haplotypes are phased at SNPs in T should determine how well they can be matched to haplotypes in the reference panel, which should in turn influence the accuracy of imputation at SNPs in U. Second, accounting for the unknown phase of the SNPs in T can be computationally expensive; if the haplotypes at these SNPs were known, most methods would be able to impute genotypes at SNPs in U more quickly. Third, many existing methods do not use all of the available information to phase the study genotypes at SNPs in T. In principle, a phasing algorithm should be able to “learn” about desirable phasing configurations for a given study individual by pooling information across the reference panel and all other individuals in the study, and the phasing accuracy should increase with the sample size; in standard practice, most imputation methods gain phasing information about each study individual only from the reference panel, and phasing accuracy does not depend on the size of the study sample.
