Statistical inference for hardy-weinberg proportions in the presence of missing genotype information

In genetic association studies, tests for Hardy-Weinberg proportions are often employed as a quality control checking procedure. Missing genotypes are typically discarded prior to testing. In this paper we show that inference for Hardy-Weinberg proportions can be biased when missing values are disca...

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Autores: Graffelman, Jan, Sánchez, Milagros, Cook, Samantha, Moreno Aguado, Víctor
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2013
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:2445/69341
Acceso en línea:https://hdl.handle.net/2445/69341
Access Level:acceso abierto
Palabra clave:Genoma humà
Estadística matemàtica
Malalties hereditàries
Human genome
Mathematical statistics
Genetic diseases
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spelling Statistical inference for hardy-weinberg proportions in the presence of missing genotype informationGraffelman, JanSánchez, MilagrosCook, SamanthaMoreno Aguado, VíctorGenoma humàEstadística matemàticaMalalties hereditàriesHuman genomeMathematical statisticsGenetic diseasesIn genetic association studies, tests for Hardy-Weinberg proportions are often employed as a quality control checking procedure. Missing genotypes are typically discarded prior to testing. In this paper we show that inference for Hardy-Weinberg proportions can be biased when missing values are discarded. We propose to use multiple imputation of missing values in order to improve inference for Hardy-Weinberg proportions. For imputation we employ a multinomial logit model that uses information from allele intensities and/or neighbouring markers. Analysis of an empirical data set of single nucleotide polymorphisms possibly related to colon cancer reveals that missing genotypes are not missing completely at random. Deviation from Hardy-Weinberg proportions is mostly due to a lack of heterozygotes. Inbreeding coefficients estimated by multiple imputation of the missings are typically lowered with respect to inbreeding coefficients estimated by discarding the missings. Accounting for missings by multiple imputation qualitatively changed the results of 10 to 17% of the statistical tests performed. Estimates of inbreeding coefficients obtained by multiple imputation showed high correlation with estimates obtained by single imputation using an external reference panel. Our conclusion is that imputation of missing data leads to improved statistical inference for Hardy-Weinberg proportions.Public Library of Science (PLoS)2016201620132016info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersion11 p.application/pdfhttps://hdl.handle.net/2445/69341Articles publicats en revistes (Ciències Clíniques)reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésReproducció del document publicat a: http://dx.doi.org/10.1371/journal.pone.0083316PLoS One, 2013, vol. 8, num. 12, p. e83316http://dx.doi.org/10.1371/journal.pone.0083316cc-by (c) Graffelman, J. et al., 2013http://creativecommons.org/licenses/by/3.0/esinfo:eu-repo/semantics/openAccessoai:recercat.cat:2445/693412026-05-29T05:05:01Z
dc.title.none.fl_str_mv Statistical inference for hardy-weinberg proportions in the presence of missing genotype information
title Statistical inference for hardy-weinberg proportions in the presence of missing genotype information
spellingShingle Statistical inference for hardy-weinberg proportions in the presence of missing genotype information
Graffelman, Jan
Genoma humà
Estadística matemàtica
Malalties hereditàries
Human genome
Mathematical statistics
Genetic diseases
title_short Statistical inference for hardy-weinberg proportions in the presence of missing genotype information
title_full Statistical inference for hardy-weinberg proportions in the presence of missing genotype information
title_fullStr Statistical inference for hardy-weinberg proportions in the presence of missing genotype information
title_full_unstemmed Statistical inference for hardy-weinberg proportions in the presence of missing genotype information
title_sort Statistical inference for hardy-weinberg proportions in the presence of missing genotype information
dc.creator.none.fl_str_mv Graffelman, Jan
Sánchez, Milagros
Cook, Samantha
Moreno Aguado, Víctor
author Graffelman, Jan
author_facet Graffelman, Jan
Sánchez, Milagros
Cook, Samantha
Moreno Aguado, Víctor
author_role author
author2 Sánchez, Milagros
Cook, Samantha
Moreno Aguado, Víctor
author2_role author
author
author
dc.subject.none.fl_str_mv Genoma humà
Estadística matemàtica
Malalties hereditàries
Human genome
Mathematical statistics
Genetic diseases
topic Genoma humà
Estadística matemàtica
Malalties hereditàries
Human genome
Mathematical statistics
Genetic diseases
description In genetic association studies, tests for Hardy-Weinberg proportions are often employed as a quality control checking procedure. Missing genotypes are typically discarded prior to testing. In this paper we show that inference for Hardy-Weinberg proportions can be biased when missing values are discarded. We propose to use multiple imputation of missing values in order to improve inference for Hardy-Weinberg proportions. For imputation we employ a multinomial logit model that uses information from allele intensities and/or neighbouring markers. Analysis of an empirical data set of single nucleotide polymorphisms possibly related to colon cancer reveals that missing genotypes are not missing completely at random. Deviation from Hardy-Weinberg proportions is mostly due to a lack of heterozygotes. Inbreeding coefficients estimated by multiple imputation of the missings are typically lowered with respect to inbreeding coefficients estimated by discarding the missings. Accounting for missings by multiple imputation qualitatively changed the results of 10 to 17% of the statistical tests performed. Estimates of inbreeding coefficients obtained by multiple imputation showed high correlation with estimates obtained by single imputation using an external reference panel. Our conclusion is that imputation of missing data leads to improved statistical inference for Hardy-Weinberg proportions.
publishDate 2013
dc.date.none.fl_str_mv 2013
2016
2016
2016
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/2445/69341
url https://hdl.handle.net/2445/69341
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Reproducció del document publicat a: http://dx.doi.org/10.1371/journal.pone.0083316
PLoS One, 2013, vol. 8, num. 12, p. e83316
http://dx.doi.org/10.1371/journal.pone.0083316
dc.rights.none.fl_str_mv cc-by (c) Graffelman, J. et al., 2013
http://creativecommons.org/licenses/by/3.0/es
info:eu-repo/semantics/openAccess
rights_invalid_str_mv cc-by (c) Graffelman, J. et al., 2013
http://creativecommons.org/licenses/by/3.0/es
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 11 p.
application/pdf
dc.publisher.none.fl_str_mv Public Library of Science (PLoS)
publisher.none.fl_str_mv Public Library of Science (PLoS)
dc.source.none.fl_str_mv Articles publicats en revistes (Ciències Clíniques)
reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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