Zero-inflated Poisson regression models for QTL mapping applied to tick-resistance in a Gyr x Holstein F2 population

Detalhes bibliográficos
Autor(a) principal: Silva,Fabyano Fonseca
Data de Publicação: 2011
Outros Autores: Tunin,Karen P., Rosa,Guilherme J.M., Silva,Marcos V.B. da, Azevedo,Ana Luisa Souza, Verneque,Rui da Silva, Machado,Marco Antonio, Packer,Irineu Umberto
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Genetics and Molecular Biology
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572011000400008
Resumo: Nowadays, an important and interesting alternative in the control of tick-infestation in cattle is to select resistant animals, and identify the respective quantitative trait loci (QTLs) and DNA markers, for posterior use in breeding programs. The number of ticks/animal is characterized as a discrete-counting trait, which could potentially follow Poisson distribution. However, in the case of an excess of zeros, due to the occurrence of several noninfected animals, zero-inflated Poisson and generalized zero-inflated distribution (GZIP) may provide a better description of the data. Thus, the objective here was to compare through simulation, Poisson and ZIP models (simple and generalized) with classical approaches, for QTL mapping with counting phenotypes under different scenarios, and to apply these approaches to a QTL study of tick resistance in an F2 cattle (Gyr x Holstein) population. It was concluded that, when working with zero-inflated data, it is recommendable to use the generalized and simple ZIP model for analysis. On the other hand, when working with data with zeros, but not zero-inflated, the Poisson model or a data-transformation-approach, such as square-root or Box-Cox transformation, are applicable.
id SBG-1_a3eff11afe303a7751233d444580440a
oai_identifier_str oai:scielo:S1415-47572011000400008
network_acronym_str SBG-1
network_name_str Genetics and Molecular Biology
repository_id_str
spelling Zero-inflated Poisson regression models for QTL mapping applied to tick-resistance in a Gyr x Holstein F2 populationdairycattletick infestationQTL regressiongeneralized linear modelNowadays, an important and interesting alternative in the control of tick-infestation in cattle is to select resistant animals, and identify the respective quantitative trait loci (QTLs) and DNA markers, for posterior use in breeding programs. The number of ticks/animal is characterized as a discrete-counting trait, which could potentially follow Poisson distribution. However, in the case of an excess of zeros, due to the occurrence of several noninfected animals, zero-inflated Poisson and generalized zero-inflated distribution (GZIP) may provide a better description of the data. Thus, the objective here was to compare through simulation, Poisson and ZIP models (simple and generalized) with classical approaches, for QTL mapping with counting phenotypes under different scenarios, and to apply these approaches to a QTL study of tick resistance in an F2 cattle (Gyr x Holstein) population. It was concluded that, when working with zero-inflated data, it is recommendable to use the generalized and simple ZIP model for analysis. On the other hand, when working with data with zeros, but not zero-inflated, the Poisson model or a data-transformation-approach, such as square-root or Box-Cox transformation, are applicable.Sociedade Brasileira de Genética2011-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572011000400008Genetics and Molecular Biology v.34 n.4 2011reponame:Genetics and Molecular Biologyinstname:Sociedade Brasileira de Genética (SBG)instacron:SBG10.1590/S1415-47572011005000049info:eu-repo/semantics/openAccessSilva,Fabyano FonsecaTunin,Karen P.Rosa,Guilherme J.M.Silva,Marcos V.B. daAzevedo,Ana Luisa SouzaVerneque,Rui da SilvaMachado,Marco AntonioPacker,Irineu Umbertoeng2011-11-11T00:00:00Zoai:scielo:S1415-47572011000400008Revistahttp://www.gmb.org.br/ONGhttps://old.scielo.br/oai/scielo-oai.php||editor@gmb.org.br1678-46851415-4757opendoar:2011-11-11T00:00Genetics and Molecular Biology - Sociedade Brasileira de Genética (SBG)false
dc.title.none.fl_str_mv Zero-inflated Poisson regression models for QTL mapping applied to tick-resistance in a Gyr x Holstein F2 population
title Zero-inflated Poisson regression models for QTL mapping applied to tick-resistance in a Gyr x Holstein F2 population
spellingShingle Zero-inflated Poisson regression models for QTL mapping applied to tick-resistance in a Gyr x Holstein F2 population
Silva,Fabyano Fonseca
dairy
cattle
tick infestation
QTL regression
generalized linear model
title_short Zero-inflated Poisson regression models for QTL mapping applied to tick-resistance in a Gyr x Holstein F2 population
title_full Zero-inflated Poisson regression models for QTL mapping applied to tick-resistance in a Gyr x Holstein F2 population
title_fullStr Zero-inflated Poisson regression models for QTL mapping applied to tick-resistance in a Gyr x Holstein F2 population
title_full_unstemmed Zero-inflated Poisson regression models for QTL mapping applied to tick-resistance in a Gyr x Holstein F2 population
title_sort Zero-inflated Poisson regression models for QTL mapping applied to tick-resistance in a Gyr x Holstein F2 population
author Silva,Fabyano Fonseca
author_facet Silva,Fabyano Fonseca
Tunin,Karen P.
Rosa,Guilherme J.M.
Silva,Marcos V.B. da
Azevedo,Ana Luisa Souza
Verneque,Rui da Silva
Machado,Marco Antonio
Packer,Irineu Umberto
author_role author
author2 Tunin,Karen P.
Rosa,Guilherme J.M.
Silva,Marcos V.B. da
Azevedo,Ana Luisa Souza
Verneque,Rui da Silva
Machado,Marco Antonio
Packer,Irineu Umberto
author2_role author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv Silva,Fabyano Fonseca
Tunin,Karen P.
Rosa,Guilherme J.M.
Silva,Marcos V.B. da
Azevedo,Ana Luisa Souza
Verneque,Rui da Silva
Machado,Marco Antonio
Packer,Irineu Umberto
dc.subject.por.fl_str_mv dairy
cattle
tick infestation
QTL regression
generalized linear model
topic dairy
cattle
tick infestation
QTL regression
generalized linear model
description Nowadays, an important and interesting alternative in the control of tick-infestation in cattle is to select resistant animals, and identify the respective quantitative trait loci (QTLs) and DNA markers, for posterior use in breeding programs. The number of ticks/animal is characterized as a discrete-counting trait, which could potentially follow Poisson distribution. However, in the case of an excess of zeros, due to the occurrence of several noninfected animals, zero-inflated Poisson and generalized zero-inflated distribution (GZIP) may provide a better description of the data. Thus, the objective here was to compare through simulation, Poisson and ZIP models (simple and generalized) with classical approaches, for QTL mapping with counting phenotypes under different scenarios, and to apply these approaches to a QTL study of tick resistance in an F2 cattle (Gyr x Holstein) population. It was concluded that, when working with zero-inflated data, it is recommendable to use the generalized and simple ZIP model for analysis. On the other hand, when working with data with zeros, but not zero-inflated, the Poisson model or a data-transformation-approach, such as square-root or Box-Cox transformation, are applicable.
publishDate 2011
dc.date.none.fl_str_mv 2011-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572011000400008
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572011000400008
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S1415-47572011005000049
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Sociedade Brasileira de Genética
publisher.none.fl_str_mv Sociedade Brasileira de Genética
dc.source.none.fl_str_mv Genetics and Molecular Biology v.34 n.4 2011
reponame:Genetics and Molecular Biology
instname:Sociedade Brasileira de Genética (SBG)
instacron:SBG
instname_str Sociedade Brasileira de Genética (SBG)
instacron_str SBG
institution SBG
reponame_str Genetics and Molecular Biology
collection Genetics and Molecular Biology
repository.name.fl_str_mv Genetics and Molecular Biology - Sociedade Brasileira de Genética (SBG)
repository.mail.fl_str_mv ||editor@gmb.org.br
_version_ 1752122384173760512