Equivalence of variance components between standard and recursive genetic models using LDL′ transformations

Abstract Background Recursive models are a category of structural equation models that propose a causal relationship between traits. These models are more parameterized than multiple trait models, and they require imposing restrictions on the parameter space to ensure statistical identification. Nev...

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Main Authors: Luis Varona, David López-Carbonell, Houssemeddine Srihi, Carlos Hervás-Rivero, Óscar González-Recio, Juan Altarriba
Format: Article
Language:deu
Published: BMC 2024-05-01
Series:Genetics Selection Evolution
Online Access:https://doi.org/10.1186/s12711-024-00901-x
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author Luis Varona
David López-Carbonell
Houssemeddine Srihi
Carlos Hervás-Rivero
Óscar González-Recio
Juan Altarriba
author_facet Luis Varona
David López-Carbonell
Houssemeddine Srihi
Carlos Hervás-Rivero
Óscar González-Recio
Juan Altarriba
author_sort Luis Varona
collection DOAJ
description Abstract Background Recursive models are a category of structural equation models that propose a causal relationship between traits. These models are more parameterized than multiple trait models, and they require imposing restrictions on the parameter space to ensure statistical identification. Nevertheless, in certain situations, the likelihood of recursive models and multiple trait models are equivalent. Consequently, the estimates of variance components derived from the multiple trait mixed model can be converted into estimates under several recursive models through LDL′ or block-LDL′ transformations. Results The procedure was employed on a dataset comprising five traits (birth weight—BW, weight at 90 days—W90, weight at 210 days—W210, cold carcass weight—CCW and conformation—CON) from the Pirenaica beef cattle breed. These phenotypic records were unequally distributed among 149,029 individuals and had a high percentage of missing data. The pedigree used consisted of 343,753 individuals. A Bayesian approach involving a multiple-trait mixed model was applied using a Gibbs sampler. The variance components obtained at each iteration of the Gibbs sampler were subsequently used to estimate the variance components within three distinct recursive models. Conclusions The LDL′ or block-LDL′ transformations applied to the variance component estimates achieved from a multiple trait mixed model enabled inference across multiple sets of recursive models, with the sole prerequisite of being likelihood equivalent. Furthermore, the aforementioned transformations simplify the handling of missing data when conducting inference within the realm of recursive models.
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publishDate 2024-05-01
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series Genetics Selection Evolution
spelling doaj-art-95f1999cfc68412fb6bc180f092a707f2025-08-20T02:50:03ZdeuBMCGenetics Selection Evolution1297-96862024-05-0156111010.1186/s12711-024-00901-xEquivalence of variance components between standard and recursive genetic models using LDL′ transformationsLuis Varona0David López-Carbonell1Houssemeddine Srihi2Carlos Hervás-Rivero3Óscar González-Recio4Juan Altarriba5Instituto Agroalimentario de Aragón (IA2), Universidad de ZaragozaInstituto Agroalimentario de Aragón (IA2), Universidad de ZaragozaInstituto Agroalimentario de Aragón (IA2), Universidad de ZaragozaInstituto Agroalimentario de Aragón (IA2), Universidad de ZaragozaInstituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA-CSIC)Instituto Agroalimentario de Aragón (IA2), Universidad de ZaragozaAbstract Background Recursive models are a category of structural equation models that propose a causal relationship between traits. These models are more parameterized than multiple trait models, and they require imposing restrictions on the parameter space to ensure statistical identification. Nevertheless, in certain situations, the likelihood of recursive models and multiple trait models are equivalent. Consequently, the estimates of variance components derived from the multiple trait mixed model can be converted into estimates under several recursive models through LDL′ or block-LDL′ transformations. Results The procedure was employed on a dataset comprising five traits (birth weight—BW, weight at 90 days—W90, weight at 210 days—W210, cold carcass weight—CCW and conformation—CON) from the Pirenaica beef cattle breed. These phenotypic records were unequally distributed among 149,029 individuals and had a high percentage of missing data. The pedigree used consisted of 343,753 individuals. A Bayesian approach involving a multiple-trait mixed model was applied using a Gibbs sampler. The variance components obtained at each iteration of the Gibbs sampler were subsequently used to estimate the variance components within three distinct recursive models. Conclusions The LDL′ or block-LDL′ transformations applied to the variance component estimates achieved from a multiple trait mixed model enabled inference across multiple sets of recursive models, with the sole prerequisite of being likelihood equivalent. Furthermore, the aforementioned transformations simplify the handling of missing data when conducting inference within the realm of recursive models.https://doi.org/10.1186/s12711-024-00901-x
spellingShingle Luis Varona
David López-Carbonell
Houssemeddine Srihi
Carlos Hervás-Rivero
Óscar González-Recio
Juan Altarriba
Equivalence of variance components between standard and recursive genetic models using LDL′ transformations
Genetics Selection Evolution
title Equivalence of variance components between standard and recursive genetic models using LDL′ transformations
title_full Equivalence of variance components between standard and recursive genetic models using LDL′ transformations
title_fullStr Equivalence of variance components between standard and recursive genetic models using LDL′ transformations
title_full_unstemmed Equivalence of variance components between standard and recursive genetic models using LDL′ transformations
title_short Equivalence of variance components between standard and recursive genetic models using LDL′ transformations
title_sort equivalence of variance components between standard and recursive genetic models using ldl transformations
url https://doi.org/10.1186/s12711-024-00901-x
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AT carloshervasrivero equivalenceofvariancecomponentsbetweenstandardandrecursivegeneticmodelsusingldltransformations
AT oscargonzalezrecio equivalenceofvariancecomponentsbetweenstandardandrecursivegeneticmodelsusingldltransformations
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