Detecting genotyping error using measures of degree of hardy-weinberg disequilibrium

Tests for Hardy-Weinberg equilibrium (HWE) have been used to detect genotyping error, but those tests have low power unless the sample size is very large. We assessed the performance of measures of departure from HWE as an alternative way of screening for genotyping error. Three measures of the degr...

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Main Authors: John Attia, Ammarin Thakkinstian, Patrick McElduff, Elizabeth Milne, Somer Dawson, Rodney J. Scott, Nicholas De Klerk, Bruce Armstrong, John Thompson
Other Authors: University of Newcastle, Australia
Format: Article
Published: 2018
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Online Access:https://repository.li.mahidol.ac.th/handle/123456789/28761
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spelling th-mahidol.287612018-09-24T16:12:48Z Detecting genotyping error using measures of degree of hardy-weinberg disequilibrium John Attia Ammarin Thakkinstian Patrick McElduff Elizabeth Milne Somer Dawson Rodney J. Scott Nicholas De Klerk Bruce Armstrong John Thompson University of Newcastle, Australia Mahidol University University of Western Australia The University of Sydney University of Leicester Biochemistry, Genetics and Molecular Biology Mathematics Tests for Hardy-Weinberg equilibrium (HWE) have been used to detect genotyping error, but those tests have low power unless the sample size is very large. We assessed the performance of measures of departure from HWE as an alternative way of screening for genotyping error. Three measures of the degree of disequilibrium (α, ,D, and F) were tested for their ability to detect genotyping error of 5% or more using simulations and a real dataset of 184 children with leukemia genotyped at 28 single nucleotide polymorphisms. The simulations indicate that all three disequilibrium coefficients can usefully detect genotyping error as judged by the area under the Receiver Operator Characteristic (ROC) curve. Their discriminative ability increases as the error rate increases, and is greater if the genotyping error is in the direction of the minor allele. Optimal thresholds for detecting genotyping error vary for different allele frequencies and patterns of genotyping error but allele frequency-specific thresholds can be nominated. Applying these thresholds would have picked up about 90% of genotyping errors in our actual dataset. Measures of departure from HWE may be useful for detecting genotyping error, but this needs to be confirmed in other real datasets. © 2010 The Berkeley Electronic Press. All rights reserved. 2018-09-24T08:47:01Z 2018-09-24T08:47:01Z 2010-03-08 Article Statistical Applications in Genetics and Molecular Biology. Vol.9, No.1 (2010) 10.2202/1544-6115.1463 15446115 2-s2.0-77649140866 https://repository.li.mahidol.ac.th/handle/123456789/28761 Mahidol University SCOPUS https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=77649140866&origin=inward
institution Mahidol University
building Mahidol University Library
continent Asia
country Thailand
Thailand
content_provider Mahidol University Library
collection Mahidol University Institutional Repository
topic Biochemistry, Genetics and Molecular Biology
Mathematics
spellingShingle Biochemistry, Genetics and Molecular Biology
Mathematics
John Attia
Ammarin Thakkinstian
Patrick McElduff
Elizabeth Milne
Somer Dawson
Rodney J. Scott
Nicholas De Klerk
Bruce Armstrong
John Thompson
Detecting genotyping error using measures of degree of hardy-weinberg disequilibrium
description Tests for Hardy-Weinberg equilibrium (HWE) have been used to detect genotyping error, but those tests have low power unless the sample size is very large. We assessed the performance of measures of departure from HWE as an alternative way of screening for genotyping error. Three measures of the degree of disequilibrium (α, ,D, and F) were tested for their ability to detect genotyping error of 5% or more using simulations and a real dataset of 184 children with leukemia genotyped at 28 single nucleotide polymorphisms. The simulations indicate that all three disequilibrium coefficients can usefully detect genotyping error as judged by the area under the Receiver Operator Characteristic (ROC) curve. Their discriminative ability increases as the error rate increases, and is greater if the genotyping error is in the direction of the minor allele. Optimal thresholds for detecting genotyping error vary for different allele frequencies and patterns of genotyping error but allele frequency-specific thresholds can be nominated. Applying these thresholds would have picked up about 90% of genotyping errors in our actual dataset. Measures of departure from HWE may be useful for detecting genotyping error, but this needs to be confirmed in other real datasets. © 2010 The Berkeley Electronic Press. All rights reserved.
author2 University of Newcastle, Australia
author_facet University of Newcastle, Australia
John Attia
Ammarin Thakkinstian
Patrick McElduff
Elizabeth Milne
Somer Dawson
Rodney J. Scott
Nicholas De Klerk
Bruce Armstrong
John Thompson
format Article
author John Attia
Ammarin Thakkinstian
Patrick McElduff
Elizabeth Milne
Somer Dawson
Rodney J. Scott
Nicholas De Klerk
Bruce Armstrong
John Thompson
author_sort John Attia
title Detecting genotyping error using measures of degree of hardy-weinberg disequilibrium
title_short Detecting genotyping error using measures of degree of hardy-weinberg disequilibrium
title_full Detecting genotyping error using measures of degree of hardy-weinberg disequilibrium
title_fullStr Detecting genotyping error using measures of degree of hardy-weinberg disequilibrium
title_full_unstemmed Detecting genotyping error using measures of degree of hardy-weinberg disequilibrium
title_sort detecting genotyping error using measures of degree of hardy-weinberg disequilibrium
publishDate 2018
url https://repository.li.mahidol.ac.th/handle/123456789/28761
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