Comparison of inference methods of genetic parameters with an application to body weight in broilers
REML (restricted maximum likelihood) has become the standard method of variance component estimation in animal breeding. Inference in Bayesian animal models is typically based upon Markov chain Monte Carlo (MCMC) methods, which are generally flexible but time-consuming. Recently, a new Bayesian com...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2015-07-01
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| Series: | Archives Animal Breeding |
| Online Access: | http://www.arch-anim-breed.net/58/277/2015/aab-58-277-2015.pdf |
| _version_ | 1819093332203143168 |
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| author | G. Maniatis N. Demiris A. Kranis G. Banos A. Kominakis |
| author_facet | G. Maniatis N. Demiris A. Kranis G. Banos A. Kominakis |
| author_sort | G. Maniatis |
| collection | DOAJ |
| description | REML (restricted maximum likelihood) has become the standard method of variance component estimation in
animal breeding. Inference in Bayesian animal models is typically based upon
Markov chain Monte Carlo (MCMC) methods, which are generally flexible but time-consuming.
Recently, a new Bayesian computational method, integrated nested
Laplace approximation (INLA), has been introduced for making fast
non-sampling-based Bayesian inference for hierarchical latent Gaussian
models. This paper is concerned with the comparison of estimates provided by
three representative programs (ASReml, WinBUGS and the R package AnimalINLA)
of the corresponding methods (REML, MCMC and INLA), with a view to their
applicability for the typical animal breeder. Gaussian and binary as well
as simulated data were used to assess the relative efficiency of the methods.
Analysis of 2319 records of body weight at 35 days of age from a broiler
line suggested a purely additive animal model, in which the heritability
estimates ranged from 0.31 to 0.34 for the Gaussian trait and from 0.19 to
0.36 for the binary trait, depending on the estimation method. Although in
need of further development, AnimalINLA seems a fast program for Bayesian
modeling, particularly suitable for the inference of Gaussian traits, while
WinBUGS appeared to successfully accommodate a complicated structure between
the random effects. However, ASReml remains the best practical choice for
the serious animal breeder. |
| first_indexed | 2024-12-21T23:09:50Z |
| format | Article |
| id | doaj.art-ed64b66caf9e4a9ba79a8ff38105b84b |
| institution | Directory Open Access Journal |
| issn | 0003-9438 2363-9822 |
| language | English |
| last_indexed | 2024-12-21T23:09:50Z |
| publishDate | 2015-07-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Archives Animal Breeding |
| spelling | doaj.art-ed64b66caf9e4a9ba79a8ff38105b84b2022-12-21T18:47:05ZengCopernicus PublicationsArchives Animal Breeding0003-94382363-98222015-07-0158227728610.5194/aab-58-277-2015Comparison of inference methods of genetic parameters with an application to body weight in broilersG. Maniatis0N. Demiris1A. Kranis2G. Banos3A. Kominakis4Faculty of Animal Science and Aquaculture, Agricultural University of Athens, Iera Odos 75, 118 55 Athens, GreeceDepartment of Statistics, Athens University of Economics and Business, 76 Patission Str., 10434 Athens, GreeceThe Roslin Institute and Royal School of Veterinary Studies, University of Edinburgh, Midlothian, EH25 9RG, Scotland, UKThe Roslin Institute and Royal School of Veterinary Studies, University of Edinburgh, Midlothian, EH25 9RG, Scotland, UKFaculty of Animal Science and Aquaculture, Agricultural University of Athens, Iera Odos 75, 118 55 Athens, GreeceREML (restricted maximum likelihood) has become the standard method of variance component estimation in animal breeding. Inference in Bayesian animal models is typically based upon Markov chain Monte Carlo (MCMC) methods, which are generally flexible but time-consuming. Recently, a new Bayesian computational method, integrated nested Laplace approximation (INLA), has been introduced for making fast non-sampling-based Bayesian inference for hierarchical latent Gaussian models. This paper is concerned with the comparison of estimates provided by three representative programs (ASReml, WinBUGS and the R package AnimalINLA) of the corresponding methods (REML, MCMC and INLA), with a view to their applicability for the typical animal breeder. Gaussian and binary as well as simulated data were used to assess the relative efficiency of the methods. Analysis of 2319 records of body weight at 35 days of age from a broiler line suggested a purely additive animal model, in which the heritability estimates ranged from 0.31 to 0.34 for the Gaussian trait and from 0.19 to 0.36 for the binary trait, depending on the estimation method. Although in need of further development, AnimalINLA seems a fast program for Bayesian modeling, particularly suitable for the inference of Gaussian traits, while WinBUGS appeared to successfully accommodate a complicated structure between the random effects. However, ASReml remains the best practical choice for the serious animal breeder.http://www.arch-anim-breed.net/58/277/2015/aab-58-277-2015.pdf |
| spellingShingle | G. Maniatis N. Demiris A. Kranis G. Banos A. Kominakis Comparison of inference methods of genetic parameters with an application to body weight in broilers Archives Animal Breeding |
| title | Comparison of inference methods of genetic parameters with an application to body weight in broilers |
| title_full | Comparison of inference methods of genetic parameters with an application to body weight in broilers |
| title_fullStr | Comparison of inference methods of genetic parameters with an application to body weight in broilers |
| title_full_unstemmed | Comparison of inference methods of genetic parameters with an application to body weight in broilers |
| title_short | Comparison of inference methods of genetic parameters with an application to body weight in broilers |
| title_sort | comparison of inference methods of genetic parameters with an application to body weight in broilers |
| url | http://www.arch-anim-breed.net/58/277/2015/aab-58-277-2015.pdf |
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