Quality control of genotypes using heritability estimates of gene content at the marker
- Autores
- Forneris, Natalia Soledad; Legarra, Andrés L.; Vitezica, Zulma G.; Tsuruta, Shogo; Aguilar, Ignacio; Misztal, Ignacy; Cantet, Rodolfo Juan Carlos
- Año de publicación
- 2015
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Quality control filtering of single nucleotide polymorphisms (SNP) is a key step when analyzing genomic data. Here, we present a practical method to identify low-quality SNPs, meaning markers whose genotypes are wrongly assigned for a large proportion of individuals, by estimating the heritability of gene content at each marker, where gene content is the number of copies of a particular reference allele in a genotype of an animal (0, 1 or 2). If there is no mutation at the marker, gene content has an additive heritability of 1 by construction. The method uses Restricted Maximum Likelihood to estimate heritability of gene content at each SNP and also builds a likelihood ratio test statistic to test for zero error variance in genotyping. As a byproduct, estimates of the allele frequencies of markers at the base population are obtained. Using simulated data with 10% permutation error (4% actual error) in genotyping, the method had a specificity of 96% (4% of correct markers are rejected) and a sensitivity of 0.99 (1% of wrong markers are accepted) if markers with heritability lower than 0.975 are discarded. Checking of Mendelian errors resulted in a lower sensitivity (0.84) for the same simulation. The proposed method is further illustrated with a real dataset with genotypes from 3,534 animals genotyped for 50,433 markers from the Illumina PorcineSNP60 chip, and a pedigree of 6,473 individuals; those markers did undergo very little quality control. A number of 4,099 markers with p-values lower than 0.01 were discarded based on our method, with associated estimates of heritability as low as 0.12. Contrary to other techniques, our method uses simultaneously all information in the population, can be used in any population with markers and pedigree recordings, and is simple to implement using standard software for REML estimation. Scripts for its use are provided.
Fil: Forneris, Natalia Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Animal. Cátedra de Mejoramiento Genético Animal; Argentina
Fil: Legarra, Andrés L.. Institut National de la Recherche Agronomique; Francia. Universite de Toulose - Le Mirail; Francia
Fil: Vitezica, Zulma G.. Universite de Toulose - Le Mirail; Francia. Institut National de la Recherche Agronomique; Francia
Fil: Tsuruta, Shogo. University of Georgia; Estados Unidos
Fil: Aguilar, Ignacio. Instituto Nacional de Investigación Agropecuaria; Uruguay
Fil: Misztal, Ignacy. University of Georgia; Estados Unidos
Fil: Cantet, Rodolfo Juan Carlos. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Animal. Cátedra de Mejoramiento Genético Animal; Argentina - Materia
-
Gene Content
Quality Control
Snp
Genomic Selection
Reml
Shared Data Resource
Genpred - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/44365
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Quality control of genotypes using heritability estimates of gene content at the markerForneris, Natalia SoledadLegarra, Andrés L.Vitezica, Zulma G.Tsuruta, ShogoAguilar, IgnacioMisztal, IgnacyCantet, Rodolfo Juan CarlosGene ContentQuality ControlSnpGenomic SelectionRemlShared Data ResourceGenpredhttps://purl.org/becyt/ford/4.2https://purl.org/becyt/ford/4Quality control filtering of single nucleotide polymorphisms (SNP) is a key step when analyzing genomic data. Here, we present a practical method to identify low-quality SNPs, meaning markers whose genotypes are wrongly assigned for a large proportion of individuals, by estimating the heritability of gene content at each marker, where gene content is the number of copies of a particular reference allele in a genotype of an animal (0, 1 or 2). If there is no mutation at the marker, gene content has an additive heritability of 1 by construction. The method uses Restricted Maximum Likelihood to estimate heritability of gene content at each SNP and also builds a likelihood ratio test statistic to test for zero error variance in genotyping. As a byproduct, estimates of the allele frequencies of markers at the base population are obtained. Using simulated data with 10% permutation error (4% actual error) in genotyping, the method had a specificity of 96% (4% of correct markers are rejected) and a sensitivity of 0.99 (1% of wrong markers are accepted) if markers with heritability lower than 0.975 are discarded. Checking of Mendelian errors resulted in a lower sensitivity (0.84) for the same simulation. The proposed method is further illustrated with a real dataset with genotypes from 3,534 animals genotyped for 50,433 markers from the Illumina PorcineSNP60 chip, and a pedigree of 6,473 individuals; those markers did undergo very little quality control. A number of 4,099 markers with p-values lower than 0.01 were discarded based on our method, with associated estimates of heritability as low as 0.12. Contrary to other techniques, our method uses simultaneously all information in the population, can be used in any population with markers and pedigree recordings, and is simple to implement using standard software for REML estimation. Scripts for its use are provided.Fil: Forneris, Natalia Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Animal. Cátedra de Mejoramiento Genético Animal; ArgentinaFil: Legarra, Andrés L.. Institut National de la Recherche Agronomique; Francia. Universite de Toulose - Le Mirail; FranciaFil: Vitezica, Zulma G.. Universite de Toulose - Le Mirail; Francia. Institut National de la Recherche Agronomique; FranciaFil: Tsuruta, Shogo. University of Georgia; Estados UnidosFil: Aguilar, Ignacio. Instituto Nacional de Investigación Agropecuaria; UruguayFil: Misztal, Ignacy. University of Georgia; Estados UnidosFil: Cantet, Rodolfo Juan Carlos. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Animal. Cátedra de Mejoramiento Genético Animal; ArgentinaGenetics Society of America2015-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/44365Forneris, Natalia Soledad; Legarra, Andrés L.; Vitezica, Zulma G.; Tsuruta, Shogo; Aguilar, Ignacio; et al.; Quality control of genotypes using heritability estimates of gene content at the marker; Genetics Society of America; Genetics; 199; 3; 3-2015; 675-6810016-67311943-2631CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://www.genetics.org/content/199/3/675info:eu-repo/semantics/altIdentifier/doi/10.1534/genetics.114.173559info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:41:54Zoai:ri.conicet.gov.ar:11336/44365instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:41:54.777CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
Quality control of genotypes using heritability estimates of gene content at the marker |
title |
Quality control of genotypes using heritability estimates of gene content at the marker |
spellingShingle |
Quality control of genotypes using heritability estimates of gene content at the marker Forneris, Natalia Soledad Gene Content Quality Control Snp Genomic Selection Reml Shared Data Resource Genpred |
title_short |
Quality control of genotypes using heritability estimates of gene content at the marker |
title_full |
Quality control of genotypes using heritability estimates of gene content at the marker |
title_fullStr |
Quality control of genotypes using heritability estimates of gene content at the marker |
title_full_unstemmed |
Quality control of genotypes using heritability estimates of gene content at the marker |
title_sort |
Quality control of genotypes using heritability estimates of gene content at the marker |
dc.creator.none.fl_str_mv |
Forneris, Natalia Soledad Legarra, Andrés L. Vitezica, Zulma G. Tsuruta, Shogo Aguilar, Ignacio Misztal, Ignacy Cantet, Rodolfo Juan Carlos |
author |
Forneris, Natalia Soledad |
author_facet |
Forneris, Natalia Soledad Legarra, Andrés L. Vitezica, Zulma G. Tsuruta, Shogo Aguilar, Ignacio Misztal, Ignacy Cantet, Rodolfo Juan Carlos |
author_role |
author |
author2 |
Legarra, Andrés L. Vitezica, Zulma G. Tsuruta, Shogo Aguilar, Ignacio Misztal, Ignacy Cantet, Rodolfo Juan Carlos |
author2_role |
author author author author author author |
dc.subject.none.fl_str_mv |
Gene Content Quality Control Snp Genomic Selection Reml Shared Data Resource Genpred |
topic |
Gene Content Quality Control Snp Genomic Selection Reml Shared Data Resource Genpred |
purl_subject.fl_str_mv |
https://purl.org/becyt/ford/4.2 https://purl.org/becyt/ford/4 |
dc.description.none.fl_txt_mv |
Quality control filtering of single nucleotide polymorphisms (SNP) is a key step when analyzing genomic data. Here, we present a practical method to identify low-quality SNPs, meaning markers whose genotypes are wrongly assigned for a large proportion of individuals, by estimating the heritability of gene content at each marker, where gene content is the number of copies of a particular reference allele in a genotype of an animal (0, 1 or 2). If there is no mutation at the marker, gene content has an additive heritability of 1 by construction. The method uses Restricted Maximum Likelihood to estimate heritability of gene content at each SNP and also builds a likelihood ratio test statistic to test for zero error variance in genotyping. As a byproduct, estimates of the allele frequencies of markers at the base population are obtained. Using simulated data with 10% permutation error (4% actual error) in genotyping, the method had a specificity of 96% (4% of correct markers are rejected) and a sensitivity of 0.99 (1% of wrong markers are accepted) if markers with heritability lower than 0.975 are discarded. Checking of Mendelian errors resulted in a lower sensitivity (0.84) for the same simulation. The proposed method is further illustrated with a real dataset with genotypes from 3,534 animals genotyped for 50,433 markers from the Illumina PorcineSNP60 chip, and a pedigree of 6,473 individuals; those markers did undergo very little quality control. A number of 4,099 markers with p-values lower than 0.01 were discarded based on our method, with associated estimates of heritability as low as 0.12. Contrary to other techniques, our method uses simultaneously all information in the population, can be used in any population with markers and pedigree recordings, and is simple to implement using standard software for REML estimation. Scripts for its use are provided. Fil: Forneris, Natalia Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Animal. Cátedra de Mejoramiento Genético Animal; Argentina Fil: Legarra, Andrés L.. Institut National de la Recherche Agronomique; Francia. Universite de Toulose - Le Mirail; Francia Fil: Vitezica, Zulma G.. Universite de Toulose - Le Mirail; Francia. Institut National de la Recherche Agronomique; Francia Fil: Tsuruta, Shogo. University of Georgia; Estados Unidos Fil: Aguilar, Ignacio. Instituto Nacional de Investigación Agropecuaria; Uruguay Fil: Misztal, Ignacy. University of Georgia; Estados Unidos Fil: Cantet, Rodolfo Juan Carlos. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Animal. Cátedra de Mejoramiento Genético Animal; Argentina |
description |
Quality control filtering of single nucleotide polymorphisms (SNP) is a key step when analyzing genomic data. Here, we present a practical method to identify low-quality SNPs, meaning markers whose genotypes are wrongly assigned for a large proportion of individuals, by estimating the heritability of gene content at each marker, where gene content is the number of copies of a particular reference allele in a genotype of an animal (0, 1 or 2). If there is no mutation at the marker, gene content has an additive heritability of 1 by construction. The method uses Restricted Maximum Likelihood to estimate heritability of gene content at each SNP and also builds a likelihood ratio test statistic to test for zero error variance in genotyping. As a byproduct, estimates of the allele frequencies of markers at the base population are obtained. Using simulated data with 10% permutation error (4% actual error) in genotyping, the method had a specificity of 96% (4% of correct markers are rejected) and a sensitivity of 0.99 (1% of wrong markers are accepted) if markers with heritability lower than 0.975 are discarded. Checking of Mendelian errors resulted in a lower sensitivity (0.84) for the same simulation. The proposed method is further illustrated with a real dataset with genotypes from 3,534 animals genotyped for 50,433 markers from the Illumina PorcineSNP60 chip, and a pedigree of 6,473 individuals; those markers did undergo very little quality control. A number of 4,099 markers with p-values lower than 0.01 were discarded based on our method, with associated estimates of heritability as low as 0.12. Contrary to other techniques, our method uses simultaneously all information in the population, can be used in any population with markers and pedigree recordings, and is simple to implement using standard software for REML estimation. Scripts for its use are provided. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015-03 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
format |
article |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://hdl.handle.net/11336/44365 Forneris, Natalia Soledad; Legarra, Andrés L.; Vitezica, Zulma G.; Tsuruta, Shogo; Aguilar, Ignacio; et al.; Quality control of genotypes using heritability estimates of gene content at the marker; Genetics Society of America; Genetics; 199; 3; 3-2015; 675-681 0016-6731 1943-2631 CONICET Digital CONICET |
url |
http://hdl.handle.net/11336/44365 |
identifier_str_mv |
Forneris, Natalia Soledad; Legarra, Andrés L.; Vitezica, Zulma G.; Tsuruta, Shogo; Aguilar, Ignacio; et al.; Quality control of genotypes using heritability estimates of gene content at the marker; Genetics Society of America; Genetics; 199; 3; 3-2015; 675-681 0016-6731 1943-2631 CONICET Digital CONICET |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/url/http://www.genetics.org/content/199/3/675 info:eu-repo/semantics/altIdentifier/doi/10.1534/genetics.114.173559 |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
dc.format.none.fl_str_mv |
application/pdf application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
Genetics Society of America |
publisher.none.fl_str_mv |
Genetics Society of America |
dc.source.none.fl_str_mv |
reponame:CONICET Digital (CONICET) instname:Consejo Nacional de Investigaciones Científicas y Técnicas |
reponame_str |
CONICET Digital (CONICET) |
collection |
CONICET Digital (CONICET) |
instname_str |
Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.name.fl_str_mv |
CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.mail.fl_str_mv |
dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar |
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1844613321170354176 |
score |
13.070432 |