Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.13/930013

OpenURL Link
Title
Detecting genotyping error using measures of degree of Hardy-Weinberg disequilibrium
Author/Creator
Attia, John;  Thakkinstian, Ammarin;  McElduff, Patrick;  Milne, Elizabeth;  Dawson, Somer;  Scott, Rodney J.;  de Klerk, Nicholas;  Armstrong, Bruce;  Thompson, John
Institution
The University of Newcastle. Faculty of Health, School of Medicine and Public Health
Description
Tests for Hardy-Weinberg equilibrium (HWE) have been used to detect genotyping error, but those tests have low power unle the sample size is very large. We aeed 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.
Relation
Statistical Applications in Genetics and Molecular Biology Vol. 9, Issue 1
Publisher Link
http://dx.doi.org/10.2202/1544-6115.1463
Date
2010
Publisher
Berkeley Electronic Press
Keyword(s)
association study;  Hardy Weinberg equilibrium;  genotyping error;  disequilibrium coefficient
Resource Type
journal article
Identifier
http://hdl.handle.net/1959.13/930013
Identifier
ISSN:1544-6115
Reviewed
Reviewed
13 Visitors 15 Hits 0 Downloads
Save/E-mail Citation
Citation Format
E-mail Address
Subject
"Statistical Applications in Genetics and Molecular Biology"
 
OR