Inferring phenotypic causal structures among body weight traits via structural equation modeling in Kurdi sheep

Detalhes bibliográficos
Autor(a) principal: Mohammadi, Yahya
Data de Publicação: 2020
Outros Autores: Saghi, Davoud Ali, Shahdadi, Ali Reza, Rosa, Guilherme Jordão de Magalhães, Mokhtari, Morteza Sattaei
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Acta Scientiarum. Animal Sciences (Online)
Texto Completo: https://periodicos.uem.br/ojs/index.php/ActaSciAnimSci/article/view/48823
Resumo: Data collected on 2550 Kurdi lambs originated from 1505 dams and 149 sires during 1991 to 2015 in Hossein Abad Kurdi Sheep Breeding Station, located in Shirvan city, North Khorasan province, North-eastern area of Iran, were used for inferring causal relationship among the body weights at birth (BW), at weaning (WW), at six-month age (6MW), at nine-month age (9MW) and yearling age (YW). The inductive causation (IC) algorithm was employed to search for causal structure among these traits. This algorithm was applied to the posterior distribution of the residual (co)variance matrix of a standard multivariate model (SMM). The causal structure detected by the IC algorithm coupling with biological prior knowledge provides a temporal recursive causal network among the studied traits. The studied traits were analyzed under three multivariate models including SMM, fully recursive multivariate model (FRM) and IC-based multivariate model (ICM) via a Bayesian approach by 100,000 iterations, thinning interval of 10 and the first 10,000 iterations as burn-in. The three considered multivariate models (SMM, FRM and ICM) were compared using deviance information criterion (DIC) and predictive ability measures including mean square of error (MSE) and Pearson's correlation coefficient between the observed and predicted values (r(y, )) of records. In general, structural equation based models (FRM and ICM) performed better than SMM in terms of lower DIC and MSE and also higher r(y, ). Among the tested models ICM had the lowest (36678.551) and SMM had the highest (36744.107)DIC values. In each case of the traits studied, the lowest MSE and the highest r(y, ) were obtained under ICM. The causal effects of BW on WW, WW on 6MW, 6MW on 9MW and 9MW on YW were statistically significant values of 1.478, 0.737, 0.776 and 0.929 kg, respectively (99% highest posterior density intervals did not include zero).
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spelling Inferring phenotypic causal structures among body weight traits via structural equation modeling in Kurdi sheepInferring phenotypic causal structures among body weight traits via structural equation modeling in Kurdi sheepcausal effects; growth traits; predictive ability; sheep.causal effects; growth traits; predictive ability; sheep.Data collected on 2550 Kurdi lambs originated from 1505 dams and 149 sires during 1991 to 2015 in Hossein Abad Kurdi Sheep Breeding Station, located in Shirvan city, North Khorasan province, North-eastern area of Iran, were used for inferring causal relationship among the body weights at birth (BW), at weaning (WW), at six-month age (6MW), at nine-month age (9MW) and yearling age (YW). The inductive causation (IC) algorithm was employed to search for causal structure among these traits. This algorithm was applied to the posterior distribution of the residual (co)variance matrix of a standard multivariate model (SMM). The causal structure detected by the IC algorithm coupling with biological prior knowledge provides a temporal recursive causal network among the studied traits. The studied traits were analyzed under three multivariate models including SMM, fully recursive multivariate model (FRM) and IC-based multivariate model (ICM) via a Bayesian approach by 100,000 iterations, thinning interval of 10 and the first 10,000 iterations as burn-in. The three considered multivariate models (SMM, FRM and ICM) were compared using deviance information criterion (DIC) and predictive ability measures including mean square of error (MSE) and Pearson's correlation coefficient between the observed and predicted values (r(y, )) of records. In general, structural equation based models (FRM and ICM) performed better than SMM in terms of lower DIC and MSE and also higher r(y, ). Among the tested models ICM had the lowest (36678.551) and SMM had the highest (36744.107)DIC values. In each case of the traits studied, the lowest MSE and the highest r(y, ) were obtained under ICM. The causal effects of BW on WW, WW on 6MW, 6MW on 9MW and 9MW on YW were statistically significant values of 1.478, 0.737, 0.776 and 0.929 kg, respectively (99% highest posterior density intervals did not include zero).Data collected on 2550 Kurdi lambs originated from 1505 dams and 149 sires during 1991 to 2015 in Hossein Abad Kurdi Sheep Breeding Station, located in Shirvan city, North Khorasan province, North-eastern area of Iran, were used for inferring causal relationship among the body weights at birth (BW), at weaning (WW), at six-month age (6MW), at nine-month age (9MW) and yearling age (YW). The inductive causation (IC) algorithm was employed to search for causal structure among these traits. This algorithm was applied to the posterior distribution of the residual (co)variance matrix of a standard multivariate model (SMM). The causal structure detected by the IC algorithm coupling with biological prior knowledge provides a temporal recursive causal network among the studied traits. The studied traits were analyzed under three multivariate models including SMM, fully recursive multivariate model (FRM) and IC-based multivariate model (ICM) via a Bayesian approach by 100,000 iterations, thinning interval of 10 and the first 10,000 iterations as burn-in. The three considered multivariate models (SMM, FRM and ICM) were compared using deviance information criterion (DIC) and predictive ability measures including mean square of error (MSE) and Pearson's correlation coefficient between the observed and predicted values (r(y, )) of records. In general, structural equation based models (FRM and ICM) performed better than SMM in terms of lower DIC and MSE and also higher r(y, ). Among the tested models ICM had the lowest (36678.551) and SMM had the highest (36744.107)DIC values. In each case of the traits studied, the lowest MSE and the highest r(y, ) were obtained under ICM. The causal effects of BW on WW, WW on 6MW, 6MW on 9MW and 9MW on YW were statistically significant values of 1.478, 0.737, 0.776 and 0.929 kg, respectively (99% highest posterior density intervals did not include zero).Editora da Universidade Estadual de Maringá2020-06-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.uem.br/ojs/index.php/ActaSciAnimSci/article/view/4882310.4025/actascianimsci.v42i1.48823Acta Scientiarum. Animal Sciences; Vol 42 (2020): Publicação contínua; e48823Acta Scientiarum. Animal Sciences; v. 42 (2020): Publicação contínua; e488231807-86721806-2636reponame:Acta Scientiarum. Animal Sciences (Online)instname:Universidade Estadual de Maringá (UEM)instacron:UEMenghttps://periodicos.uem.br/ojs/index.php/ActaSciAnimSci/article/view/48823/751375150187Copyright (c) 2020 Acta Scientiarum. Animal Scienceshttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessMohammadi, YahyaSaghi, Davoud AliShahdadi, Ali RezaRosa, Guilherme Jordão de MagalhãesMokhtari, Morteza Sattaei2020-11-16T18:33:10Zoai:periodicos.uem.br/ojs:article/48823Revistahttp://www.periodicos.uem.br/ojs/index.php/ActaSciAnimSciPUBhttp://www.periodicos.uem.br/ojs/index.php/ActaSciAnimSci/oaiactaanim@uem.br||actaanim@uem.br|| rev.acta@gmail.com1807-86721806-2636opendoar:2020-11-16T18:33:10Acta Scientiarum. Animal Sciences (Online) - Universidade Estadual de Maringá (UEM)false
dc.title.none.fl_str_mv Inferring phenotypic causal structures among body weight traits via structural equation modeling in Kurdi sheep
Inferring phenotypic causal structures among body weight traits via structural equation modeling in Kurdi sheep
title Inferring phenotypic causal structures among body weight traits via structural equation modeling in Kurdi sheep
spellingShingle Inferring phenotypic causal structures among body weight traits via structural equation modeling in Kurdi sheep
Mohammadi, Yahya
causal effects; growth traits; predictive ability; sheep.
causal effects; growth traits; predictive ability; sheep.
title_short Inferring phenotypic causal structures among body weight traits via structural equation modeling in Kurdi sheep
title_full Inferring phenotypic causal structures among body weight traits via structural equation modeling in Kurdi sheep
title_fullStr Inferring phenotypic causal structures among body weight traits via structural equation modeling in Kurdi sheep
title_full_unstemmed Inferring phenotypic causal structures among body weight traits via structural equation modeling in Kurdi sheep
title_sort Inferring phenotypic causal structures among body weight traits via structural equation modeling in Kurdi sheep
author Mohammadi, Yahya
author_facet Mohammadi, Yahya
Saghi, Davoud Ali
Shahdadi, Ali Reza
Rosa, Guilherme Jordão de Magalhães
Mokhtari, Morteza Sattaei
author_role author
author2 Saghi, Davoud Ali
Shahdadi, Ali Reza
Rosa, Guilherme Jordão de Magalhães
Mokhtari, Morteza Sattaei
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Mohammadi, Yahya
Saghi, Davoud Ali
Shahdadi, Ali Reza
Rosa, Guilherme Jordão de Magalhães
Mokhtari, Morteza Sattaei
dc.subject.por.fl_str_mv causal effects; growth traits; predictive ability; sheep.
causal effects; growth traits; predictive ability; sheep.
topic causal effects; growth traits; predictive ability; sheep.
causal effects; growth traits; predictive ability; sheep.
description Data collected on 2550 Kurdi lambs originated from 1505 dams and 149 sires during 1991 to 2015 in Hossein Abad Kurdi Sheep Breeding Station, located in Shirvan city, North Khorasan province, North-eastern area of Iran, were used for inferring causal relationship among the body weights at birth (BW), at weaning (WW), at six-month age (6MW), at nine-month age (9MW) and yearling age (YW). The inductive causation (IC) algorithm was employed to search for causal structure among these traits. This algorithm was applied to the posterior distribution of the residual (co)variance matrix of a standard multivariate model (SMM). The causal structure detected by the IC algorithm coupling with biological prior knowledge provides a temporal recursive causal network among the studied traits. The studied traits were analyzed under three multivariate models including SMM, fully recursive multivariate model (FRM) and IC-based multivariate model (ICM) via a Bayesian approach by 100,000 iterations, thinning interval of 10 and the first 10,000 iterations as burn-in. The three considered multivariate models (SMM, FRM and ICM) were compared using deviance information criterion (DIC) and predictive ability measures including mean square of error (MSE) and Pearson's correlation coefficient between the observed and predicted values (r(y, )) of records. In general, structural equation based models (FRM and ICM) performed better than SMM in terms of lower DIC and MSE and also higher r(y, ). Among the tested models ICM had the lowest (36678.551) and SMM had the highest (36744.107)DIC values. In each case of the traits studied, the lowest MSE and the highest r(y, ) were obtained under ICM. The causal effects of BW on WW, WW on 6MW, 6MW on 9MW and 9MW on YW were statistically significant values of 1.478, 0.737, 0.776 and 0.929 kg, respectively (99% highest posterior density intervals did not include zero).
publishDate 2020
dc.date.none.fl_str_mv 2020-06-08
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://periodicos.uem.br/ojs/index.php/ActaSciAnimSci/article/view/48823
10.4025/actascianimsci.v42i1.48823
url https://periodicos.uem.br/ojs/index.php/ActaSciAnimSci/article/view/48823
identifier_str_mv 10.4025/actascianimsci.v42i1.48823
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://periodicos.uem.br/ojs/index.php/ActaSciAnimSci/article/view/48823/751375150187
dc.rights.driver.fl_str_mv Copyright (c) 2020 Acta Scientiarum. Animal Sciences
https://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2020 Acta Scientiarum. Animal Sciences
https://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Editora da Universidade Estadual de Maringá
publisher.none.fl_str_mv Editora da Universidade Estadual de Maringá
dc.source.none.fl_str_mv Acta Scientiarum. Animal Sciences; Vol 42 (2020): Publicação contínua; e48823
Acta Scientiarum. Animal Sciences; v. 42 (2020): Publicação contínua; e48823
1807-8672
1806-2636
reponame:Acta Scientiarum. Animal Sciences (Online)
instname:Universidade Estadual de Maringá (UEM)
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instname_str Universidade Estadual de Maringá (UEM)
instacron_str UEM
institution UEM
reponame_str Acta Scientiarum. Animal Sciences (Online)
collection Acta Scientiarum. Animal Sciences (Online)
repository.name.fl_str_mv Acta Scientiarum. Animal Sciences (Online) - Universidade Estadual de Maringá (UEM)
repository.mail.fl_str_mv actaanim@uem.br||actaanim@uem.br|| rev.acta@gmail.com
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