title: Correcting for Sample Contamination in Genotype Calling of DNA Sequence Data.
abstract: DNA sample contamination is a frequent problem in DNA sequencing studies and can result in genotyping errors and reduced power for association testing. We recently described methods to identify within-species DNA sample contamination based on sequencing read data, showed that our methods can reliably detect and estimate contamination levels as low as 1%, and suggested strategies to identify and remove contaminated samples from sequencing studies. Here we propose methods to model contamination during genotype calling as an alternative to removal of contaminated samples from further analyses. We compare our contamination-adjusted calls to calls that ignore contamination and to calls based on uncontaminated data. We demonstrate that, for moderate contamination levels (5%-20%), contamination-adjusted calls eliminate 48%-77% of the genotyping errors. For lower levels of contamination, our contamination correction methods produce genotypes nearly as accurate as those based on uncontaminated data. Our contamination correction methods are useful generally, but are particularly helpful for sample contamination levels from 2% to 20%.
authors.affiliation: Department of Biostatistics and Center for Statistical Genetics, University of Michigan, School of Public Health, 1415 Washington Heights, Ann Arbor, MI 48109, USA.
authors.forename: Matthew
authors.initials: M
authors.lastname: Flickinger
authors.affiliation: Department of Biostatistics and Center for Statistical Genetics, University of Michigan, School of Public Health, 1415 Washington Heights, Ann Arbor, MI 48109, USA; Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, 7000 Fannin Street, Houston, TX 77030, USA.
authors.forename: Goo
authors.initials: G
authors.lastname: Jun
authors.affiliation: Department of Biostatistics and Center for Statistical Genetics, University of Michigan, School of Public Health, 1415 Washington Heights, Ann Arbor, MI 48109, USA.
authors.forename: Gonçalo R
authors.initials: GR
authors.lastname: Abecasis
authors.affiliation: Department of Biostatistics and Center for Statistical Genetics, University of Michigan, School of Public Health, 1415 Washington Heights, Ann Arbor, MI 48109, USA. Electronic address: boehnke@umich.edu.
authors.forename: Michael
authors.initials: M
authors.lastname: Boehnke
authors.affiliation: Department of Biostatistics and Center for Statistical Genetics, University of Michigan, School of Public Health, 1415 Washington Heights, Ann Arbor, MI 48109, USA. Electronic address: hmkang@umich.edu.
authors.forename: Hyun Min
authors.initials: HM
authors.lastname: Kang
mesh_terms: D059018:DNA Contamination; D060005:Genotyping Techniques / Q000379:methods* / Q000592:standards*; D008957:Models, Genetic; D017422:Sequence Analysis, DNA / Q000379:methods* / Q000592:standards*