A BAYESIAN-APPROACH TO THE INFERENCE OF DIPLOID GENOTYPES USING HAPLOID GENOTYPES

Morris and Spieth (1978) described a method of calculating unbiased es timates of diploid genotype frequencies given information on the genot ypes of haploid cells derived from diploid individuals. They concluded that three haploids per diploid would minimize sampling variance of g enotype frequencies, given a fixed total number of haploids examined. If the identity of individual diploid genotypes is needed, Morris and Spieth (1978) stated that more haploids should be collected per diploi d. We extend this work by showing from a Bayesian perspective that the probability of misclassification of individuals depends not only on t he number of haploids sampled, but also on the genetic structure of th e population since misclassification error will increase as the freque ncy of heterozygotes increases. Since information on the genetic struc ture (allele frequencies, inbreeding coefficient) of a population is r arely known prior to the initiation of an empirical study, the usefuln ess of our Bayesian approach is in experimental design, by revealing t he magnitude of possible misclassification errors given a particular c hoice of number of haploids.