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Approximation of reliabilities for random-regression single-step genomic best linear unbiased predictor models.

ABSTRACT.- Random-regression models (RRM) are used in national genetic evaluations for longitudinal traits. The outputs of RRM are an index based on random-regression coefficients and its reliability. The reliabilities are obtained from the inverse of the coefficient matrix of mixed model equations...

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Main Author: BERMANN, M. (author)
Other Authors: AGUILAR, I. (author), ALVAREZ MUNERA, A. (author), BAUER, J. (author), SPLÍCHAL, J. (author), LOURENCO, D. (author), MISZTAL, I. (author)
Format: article
Language:English
Published: 2024
Subjects:
Random-regression models (RRM)
Mixed model equations (MME)
GBLUP model
SISTEMA LECHERO - INIA
Online Access:https://ainfo.inia.uy/consulta/busca?b=pc&id=64974&biblioteca=vazio&busca=64974&qFacets=64974
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author BERMANN, M.
author2 AGUILAR, I.
ALVAREZ MUNERA, A.
BAUER, J.
SPLÍCHAL, J.
LOURENCO, D.
MISZTAL, I.
author2_role author
author
author
author
author
author
author_browse AGUILAR, I.
ALVAREZ MUNERA, A.
BAUER, J.
BERMANN, M.
LOURENCO, D.
MISZTAL, I.
SPLÍCHAL, J.
author_facet BERMANN, M.
AGUILAR, I.
ALVAREZ MUNERA, A.
BAUER, J.
SPLÍCHAL, J.
LOURENCO, D.
MISZTAL, I.
author_role author
collection AINFO
dc.creator.none.fl_str_mv BERMANN, M.
AGUILAR, I.
ALVAREZ MUNERA, A.
BAUER, J.
SPLÍCHAL, J.
LOURENCO, D.
MISZTAL, I.
dc.date.none.fl_str_mv 2024
2025-06-23T18:46:03Z
2025-06-23T18:46:03Z
2025-06-23T18:46:02Z
dc.identifier.none.fl_str_mv https://ainfo.inia.uy/consulta/busca?b=pc&id=64974&biblioteca=vazio&busca=64974&qFacets=64974
dc.language.none.fl_str_mv en
eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
Acceso abierto
dc.source.none.fl_str_mv reponame:AINFO
instname:Instituto Nacional de Investigación Agropecuaria
instacron:Instituto Nacional de Investigación Agropecuaria
dc.subject.none.fl_str_mv Random-regression models (RRM)
Mixed model equations (MME)
GBLUP model
SISTEMA LECHERO - INIA
dc.title.none.fl_str_mv Approximation of reliabilities for random-regression single-step genomic best linear unbiased predictor models.
dc.type.none.fl_str_mv Article
PublishedVersion
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
description ABSTRACT.- Random-regression models (RRM) are used in national genetic evaluations for longitudinal traits. The outputs of RRM are an index based on random-regression coefficients and its reliability. The reliabilities are obtained from the inverse of the coefficient matrix of mixed model equations (MME). The reliabilities must be approximated for large datasets because it is impossible to invert the MME. There is no extensive literature on methods to approximate the reliabilities of RRM when genomic information is included by single-step GBLUP. We developed an algorithm to approximate such reliabilities. Our method combines the reliability of the index without genomic information with the reliability of a GBLUP model in terms of effective record contributions. We tested our algorithm in the 3-lactation model for milk yield from the Czech Republic. The data had 30 million test-day records, 2.5 million animals in the pedigree, and 54,000 genotyped animals. The correlation between our approximation and the reliabilities obtained from the inversion of the MME was 0.98, and the slope and intercept of the regression were 0.91 and 0.02, respectively. The elapsed time to approximate the reliabilities for the Czech data was 21 min. © 2024, The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®.
eu_rights_str_mv openAccess
format article
id anni_3d9f4ebb9798ccda9b5b80b24e7441d3
instacron_str Instituto Nacional de Investigación Agropecuaria
institution Instituto Nacional de Investigación Agropecuaria
instname_str Instituto Nacional de Investigación Agropecuaria
language eng
language_invalid_str_mv en
network_acronym_str anni
network_name_str oai-lr-anni
oai_identifier_str oai:redi.anii.org.uy:20.500.12381/4953
publishDate 2024
publishDateSort 2024
reponame_str AINFO
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
rights_invalid_str_mv Acceso abierto
spelling Approximation of reliabilities for random-regression single-step genomic best linear unbiased predictor models.BERMANN, M.AGUILAR, I.ALVAREZ MUNERA, A.BAUER, J.SPLÍCHAL, J.LOURENCO, D.MISZTAL, I.Random-regression models (RRM)Mixed model equations (MME)GBLUP modelSISTEMA LECHERO - INIAABSTRACT.- Random-regression models (RRM) are used in national genetic evaluations for longitudinal traits. The outputs of RRM are an index based on random-regression coefficients and its reliability. The reliabilities are obtained from the inverse of the coefficient matrix of mixed model equations (MME). The reliabilities must be approximated for large datasets because it is impossible to invert the MME. There is no extensive literature on methods to approximate the reliabilities of RRM when genomic information is included by single-step GBLUP. We developed an algorithm to approximate such reliabilities. Our method combines the reliability of the index without genomic information with the reliability of a GBLUP model in terms of effective record contributions. We tested our algorithm in the 3-lactation model for milk yield from the Czech Republic. The data had 30 million test-day records, 2.5 million animals in the pedigree, and 54,000 genotyped animals. The correlation between our approximation and the reliabilities obtained from the inversion of the MME was 0.98, and the slope and intercept of the regression were 0.91 and 0.02, respectively. The elapsed time to approximate the reliabilities for the Czech data was 21 min. © 2024, The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®.2025-06-23T18:46:03Z2025-06-23T18:46:03Z20242025-06-23T18:46:02ZArticlePublishedVersioninfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttps://ainfo.inia.uy/consulta/busca?b=pc&id=64974&biblioteca=vazio&busca=64974&qFacets=64974reponame:AINFOinstname:Instituto Nacional de Investigación Agropecuariainstacron:Instituto Nacional de Investigación Agropecuariaenenginfo:eu-repo/semantics/openAccessAcceso abiertooai:redi.anii.org.uy:20.500.12381/49532026-02-10T17:36:06Z
spellingShingle Approximation of reliabilities for random-regression single-step genomic best linear unbiased predictor models.
BERMANN, M.
Random-regression models (RRM)
Mixed model equations (MME)
GBLUP model
SISTEMA LECHERO - INIA
status_str publishedVersion
title Approximation of reliabilities for random-regression single-step genomic best linear unbiased predictor models.
title_full Approximation of reliabilities for random-regression single-step genomic best linear unbiased predictor models.
title_fullStr Approximation of reliabilities for random-regression single-step genomic best linear unbiased predictor models.
title_full_unstemmed Approximation of reliabilities for random-regression single-step genomic best linear unbiased predictor models.
title_short Approximation of reliabilities for random-regression single-step genomic best linear unbiased predictor models.
title_sort Approximation of reliabilities for random-regression single-step genomic best linear unbiased predictor models.
topic Random-regression models (RRM)
Mixed model equations (MME)
GBLUP model
SISTEMA LECHERO - INIA
url https://ainfo.inia.uy/consulta/busca?b=pc&id=64974&biblioteca=vazio&busca=64974&qFacets=64974

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