title: Analyzing the potential for incorrect haplotype calls with different pharmacogenomic assays in different populations: a simulation based on 1000 Genomes data.
abstract: OBJECTIVE
  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.
  
  
  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.
  
  
  CONCLUSIONS
  Haplotype nomenclatures and inference algorithms need to be improved to adequately capture pharmacogenomic diversity in human populations.
authors.affiliation: Section for Medical Expert & Knowledge-Based Systems, Center for Medical Statistics, Informatics & Intelligent Systems, Medical University of Vienna, Spitalgasse 23, 1090 Vienna, Austria.
authors.forename: Matthias
authors.initials: M
authors.lastname: Samwald
authors.affiliation: Section for Medical Expert & Knowledge-Based Systems, Center for Medical Statistics, Informatics & Intelligent Systems, Medical University of Vienna, Spitalgasse 23, 1090 Vienna, Austria.
authors.forename: Kathrin
authors.initials: K
authors.lastname: Blagec
authors.affiliation: Section for Medical Expert & Knowledge-Based Systems, Center for Medical Statistics, Informatics & Intelligent Systems, Medical University of Vienna, Spitalgasse 23, 1090 Vienna, Austria.
authors.forename: Sebastian
authors.initials: S
authors.lastname: Hofer
authors.affiliation: Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA.
authors.forename: Robert R
authors.initials: RR
authors.lastname: Freimuth
mesh_terms: D000465:Algorithms; D000483:Alleles; D030541:Databases, Genetic; D005787:Gene Frequency; D006239:Haplotypes; D006801:Humans; D010597:Pharmacogenetics / Q000379:methods*; D011110:Polymorphism, Genetic / Q000235:genetics; D044382:Population Groups; D009626:Terminology as Topic
keywords: errors; genetic diversity; genetic testing; medical nomenclature; pharmacogenomics