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Assessing the Impact of Differential Genotyping Errors on Rare Variant Tests of Association

Genotyping errors are well-known to impact the power and type I error rate in single marker tests of association. Genotyping errors that happen according to the same process in cases and controls are known as non-differential genotyping errors, whereas genotyping errors that occur with different pro...

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Autores principales: Mayer-Jochimsen, Morgan, Fast, Shannon, Tintle, Nathan L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3589406/
https://www.ncbi.nlm.nih.gov/pubmed/23472072
http://dx.doi.org/10.1371/journal.pone.0056626
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author Mayer-Jochimsen, Morgan
Fast, Shannon
Tintle, Nathan L.
author_facet Mayer-Jochimsen, Morgan
Fast, Shannon
Tintle, Nathan L.
author_sort Mayer-Jochimsen, Morgan
collection PubMed
description Genotyping errors are well-known to impact the power and type I error rate in single marker tests of association. Genotyping errors that happen according to the same process in cases and controls are known as non-differential genotyping errors, whereas genotyping errors that occur with different processes in the cases and controls are known as differential genotype errors. For single marker tests, non-differential genotyping errors reduce power, while differential genotyping errors increase the type I error rate. However, little is known about the behavior of the new generation of rare variant tests of association in the presence of genotyping errors. In this manuscript we use a comprehensive simulation study to explore the effects of numerous factors on the type I error rate of rare variant tests of association in the presence of differential genotyping error. We find that increased sample size, decreased minor allele frequency, and an increased number of single nucleotide variants (SNVs) included in the test all increase the type I error rate in the presence of differential genotyping errors. We also find that the greater the relative difference in case-control genotyping error rates the larger the type I error rate. Lastly, as is the case for single marker tests, genotyping errors classifying the common homozygote as the heterozygote inflate the type I error rate significantly more than errors classifying the heterozygote as the common homozygote. In general, our findings are in line with results from single marker tests. To ensure that type I error inflation does not occur when analyzing next-generation sequencing data careful consideration of study design (e.g. use of randomization), caution in meta-analysis and using publicly available controls, and the use of standard quality control metrics is critical.
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spelling pubmed-35894062013-03-07 Assessing the Impact of Differential Genotyping Errors on Rare Variant Tests of Association Mayer-Jochimsen, Morgan Fast, Shannon Tintle, Nathan L. PLoS One Research Article Genotyping errors are well-known to impact the power and type I error rate in single marker tests of association. Genotyping errors that happen according to the same process in cases and controls are known as non-differential genotyping errors, whereas genotyping errors that occur with different processes in the cases and controls are known as differential genotype errors. For single marker tests, non-differential genotyping errors reduce power, while differential genotyping errors increase the type I error rate. However, little is known about the behavior of the new generation of rare variant tests of association in the presence of genotyping errors. In this manuscript we use a comprehensive simulation study to explore the effects of numerous factors on the type I error rate of rare variant tests of association in the presence of differential genotyping error. We find that increased sample size, decreased minor allele frequency, and an increased number of single nucleotide variants (SNVs) included in the test all increase the type I error rate in the presence of differential genotyping errors. We also find that the greater the relative difference in case-control genotyping error rates the larger the type I error rate. Lastly, as is the case for single marker tests, genotyping errors classifying the common homozygote as the heterozygote inflate the type I error rate significantly more than errors classifying the heterozygote as the common homozygote. In general, our findings are in line with results from single marker tests. To ensure that type I error inflation does not occur when analyzing next-generation sequencing data careful consideration of study design (e.g. use of randomization), caution in meta-analysis and using publicly available controls, and the use of standard quality control metrics is critical. Public Library of Science 2013-03-05 /pmc/articles/PMC3589406/ /pubmed/23472072 http://dx.doi.org/10.1371/journal.pone.0056626 Text en © 2013 Mayer-Jochimsen et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Mayer-Jochimsen, Morgan
Fast, Shannon
Tintle, Nathan L.
Assessing the Impact of Differential Genotyping Errors on Rare Variant Tests of Association
title Assessing the Impact of Differential Genotyping Errors on Rare Variant Tests of Association
title_full Assessing the Impact of Differential Genotyping Errors on Rare Variant Tests of Association
title_fullStr Assessing the Impact of Differential Genotyping Errors on Rare Variant Tests of Association
title_full_unstemmed Assessing the Impact of Differential Genotyping Errors on Rare Variant Tests of Association
title_short Assessing the Impact of Differential Genotyping Errors on Rare Variant Tests of Association
title_sort assessing the impact of differential genotyping errors on rare variant tests of association
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3589406/
https://www.ncbi.nlm.nih.gov/pubmed/23472072
http://dx.doi.org/10.1371/journal.pone.0056626
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