The final step in the analysis of imputed data is to analyze the resulting imputed “genotypes”. MACH and other genotype imputation programs summarize imputation results in a variety of forms. Most often, imputed genotypes are not discrete but, instead, probabilistic. For example, a particular individual might have a 90% probability of carrying genotype A/A and a 10% probability of carrying genotype A/C at a specific marker – corresponding to 1.9 expected copies of allele A. We do not recommend transforming these “probabilistic” genotype calls into discrete genotypes as that can result in a substantial loss of information – especially so for less common alleles. Most often, imputed allele counts for each allele (e.g. 1.9 expected copies of allele A) can conveniently be tested for association with quantitative or discrete traits using an appropriate regression model. Of course, as in other genetic association analyses, adequate adjustment for potential population stratification is essential (27, 36, 78). If ancestry informative principal components are estimated from genetic data (78), we recommend that these should be estimated before imputation.
