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Distinct Error Rates for Reference and Nonreference Genotypes Estimated by Pedigree Analysis

Overview
Journal Genetics
Specialty Genetics
Date 2021 Mar 8
PMID 33683359
Citations 9
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Abstract

Errors in genotype calling can have perverse effects on genetic analyses, confounding association studies, and obscuring rare variants. Analyses now routinely incorporate error rates to control for spurious findings. However, reliable estimates of the error rate can be difficult to obtain because of their variance between studies. Most studies also report only a single estimate of the error rate even though genotypes can be miscalled in more than one way. Here, we report a method for estimating the rates at which different types of genotyping errors occur at biallelic loci using pedigree information. Our method identifies potential genotyping errors by exploiting instances where the haplotypic phase has not been faithfully transmitted. The expected frequency of inconsistent phase depends on the combination of genotypes in a pedigree and the probability of miscalling each genotype. We develop a model that uses the differences in these frequencies to estimate rates for different types of genotype error. Simulations show that our method accurately estimates these error rates in a variety of scenarios. We apply this method to a dataset from the whole-genome sequencing of owl monkeys (Aotus nancymaae) in three-generation pedigrees. We find significant differences between estimates for different types of genotyping error, with the most common being homozygous reference sites miscalled as heterozygous and vice versa. The approach we describe is applicable to any set of genotypes where haplotypic phase can reliably be called and should prove useful in helping to control for false discoveries.

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References
1.
Cartwright D, Troggio M, Velasco R, Gutin A . Genetic mapping in the presence of genotyping errors. Genetics. 2007; 176(4):2521-7. PMC: 1950651. DOI: 10.1534/genetics.106.063982. View

2.
Francioli L, Cretu-Stancu M, Garimella K, Fromer M, Kloosterman W, Samocha K . A framework for the detection of de novo mutations in family-based sequencing data. Eur J Hum Genet. 2016; 25(2):227-233. PMC: 5255947. DOI: 10.1038/ejhg.2016.147. View

3.
Nielsen R, Paul J, Albrechtsen A, Song Y . Genotype and SNP calling from next-generation sequencing data. Nat Rev Genet. 2011; 12(6):443-51. PMC: 3593722. DOI: 10.1038/nrg2986. View

4.
Fledel-Alon A, Wilson D, Broman K, Wen X, Ober C, Coop G . Broad-scale recombination patterns underlying proper disjunction in humans. PLoS Genet. 2009; 5(9):e1000658. PMC: 2734982. DOI: 10.1371/journal.pgen.1000658. View

5.
Ahn K, Haynes C, Kim W, St Fleur R, Gordon D, Finch S . The effects of SNP genotyping errors on the power of the Cochran-Armitage linear trend test for case/control association studies. Ann Hum Genet. 2006; 71(Pt 2):249-61. DOI: 10.1111/j.1469-1809.2006.00318.x. View