Analyzing the potential for incorrect haplotype calls with different pharmacogenomic assays in different populations: a simulation based on 1000 Genomes data. (October 2015) - Samwald, Matthias; Blagec, Kathrin; Hofer, Sebastian; Freimuth, Robert R
Aim: Many currently available pharmacogenomic assays and algorithms interrogate a set of 'tag' polymorphisms for inferring haplotypes. We wanted to test the accuracy of such haplotype inferences across different populations.Materials & methods: We simulated haplotype inferences made by existing pharmacogenomic assays for seven important pharmacogenes based on full genome data of 2504 persons in the 1000 Genomes dataset.Results: A sizable fraction of samples did not match any of the haplotypes in the star allele nomenclature systems. We found no clear population bias in the accuracy of results of simulated assays.Conclusion: Haplotype nomenclatures and inference algorithms need to be improved to adequately capture pharmacogenomic diversity in human populations.