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Registro Completo |
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Biblioteca(s): |
Embrapa Florestas. |
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Data corrente: |
03/01/2018 |
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Data da última atualização: |
11/01/2018 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
NASCIMENTO, M.; SILVA, F. F. e; RESENDE, M. D. V. de; CRUZ, C. D.; NASCIMENTO, A. C. C.; VIANA, J. M. S.; AZEVEDO, C. F.; BARROSO, L. M. A. |
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Afiliação: |
M. Nascimento, UFV; F. F. e Silva, UFV; MARCOS DEON VILELA DE RESENDE, CNPF; C. D. Cruz, UFV; A. C. C. Nascimento, UFV; J. M. S. Viana, UFV; C. F. Azevedo, UFV; L. M. A. Barroso, UFV. |
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Título: |
Regularized quantile regression applied to genome-enabled prediction of quantitative traits. |
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Ano de publicação: |
2017 |
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Fonte/Imprenta: |
Genetics and Molecular Research, v. 16, n. 1, gmr16019538, 2017. |
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Páginas: |
12 p. |
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Idioma: |
Inglês |
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Conteúdo: |
Genomic selection (GS) is a variant of marker-assisted selection, in which genetic markers covering the whole genome predict individual genetic merits for breeding. GS increases the accuracy of breeding values (BV) prediction. Although a variety of statistical models have been proposed to estimate BV in GS, few methodologies have examined statistical challenges based on non-normal phenotypic distributions, e.g., skewed distributions. Traditional GS models estimate changes in the phenotype distribution mean, i.e., the function is defined for the expected value of trait-conditional on markers, E(Y|X). We proposed an approach based on regularized quantile regression (RQR) for GS to improve the estimation of marker effects and the consequent genomic estimated BV (GEBV). The RQR model is based on conditional quantiles, Qt(Y|X), enabling models that fit all portions of a trait probability distribution. This allows RQR to choose one quantile function that ?best? represents the relationship between the dependent and independent variables. Data were simulated for 1000 individuals. The genome included 1500 markers; most had a small effect and only a few markers with a sizable effect were simulated. We evaluated three scenarios according to symmetrical, positively, and negatively skewed distributions. Analyses were performed using Bayesian LASSO (BLASSO) and RQR considering three quantiles (0.25, 0.50, and 0.75). The use of RQR to estimate GEBV was efficient; the RQR method achieved better results than BLASSO, at least for one quantile model fit for all evaluated scenarios. The gains in relation to BLASSO were 86.28 and 55.70% for positively and negatively skewed distributions, respectively. MenosGenomic selection (GS) is a variant of marker-assisted selection, in which genetic markers covering the whole genome predict individual genetic merits for breeding. GS increases the accuracy of breeding values (BV) prediction. Although a variety of statistical models have been proposed to estimate BV in GS, few methodologies have examined statistical challenges based on non-normal phenotypic distributions, e.g., skewed distributions. Traditional GS models estimate changes in the phenotype distribution mean, i.e., the function is defined for the expected value of trait-conditional on markers, E(Y|X). We proposed an approach based on regularized quantile regression (RQR) for GS to improve the estimation of marker effects and the consequent genomic estimated BV (GEBV). The RQR model is based on conditional quantiles, Qt(Y|X), enabling models that fit all portions of a trait probability distribution. This allows RQR to choose one quantile function that ?best? represents the relationship between the dependent and independent variables. Data were simulated for 1000 individuals. The genome included 1500 markers; most had a small effect and only a few markers with a sizable effect were simulated. We evaluated three scenarios according to symmetrical, positively, and negatively skewed distributions. Analyses were performed using Bayesian LASSO (BLASSO) and RQR considering three quantiles (0.25, 0.50, and 0.75). The use of RQR to estimate GEBV was efficient; the RQR method achieved be... Mostrar Tudo |
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Palavras-Chave: |
Genomic selection; Regularized regression; Seleção genômica; SNP effects. |
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Thesagro: |
Estatística. |
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Thesaurus Nal: |
Marker-assisted selection; Simulation models; Statistics. |
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Categoria do assunto: |
G Melhoramento Genético |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/170209/1/2017-M.Deon-GMR-Regularized.pdf
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Marc: |
LEADER 02634naa a2200313 a 4500
001 2084109
005 2018-01-11
008 2017 bl uuuu u00u1 u #d
100 1 $aNASCIMENTO, M.
245 $aRegularized quantile regression applied to genome-enabled prediction of quantitative traits.$h[electronic resource]
260 $c2017
300 $a12 p.
520 $aGenomic selection (GS) is a variant of marker-assisted selection, in which genetic markers covering the whole genome predict individual genetic merits for breeding. GS increases the accuracy of breeding values (BV) prediction. Although a variety of statistical models have been proposed to estimate BV in GS, few methodologies have examined statistical challenges based on non-normal phenotypic distributions, e.g., skewed distributions. Traditional GS models estimate changes in the phenotype distribution mean, i.e., the function is defined for the expected value of trait-conditional on markers, E(Y|X). We proposed an approach based on regularized quantile regression (RQR) for GS to improve the estimation of marker effects and the consequent genomic estimated BV (GEBV). The RQR model is based on conditional quantiles, Qt(Y|X), enabling models that fit all portions of a trait probability distribution. This allows RQR to choose one quantile function that ?best? represents the relationship between the dependent and independent variables. Data were simulated for 1000 individuals. The genome included 1500 markers; most had a small effect and only a few markers with a sizable effect were simulated. We evaluated three scenarios according to symmetrical, positively, and negatively skewed distributions. Analyses were performed using Bayesian LASSO (BLASSO) and RQR considering three quantiles (0.25, 0.50, and 0.75). The use of RQR to estimate GEBV was efficient; the RQR method achieved better results than BLASSO, at least for one quantile model fit for all evaluated scenarios. The gains in relation to BLASSO were 86.28 and 55.70% for positively and negatively skewed distributions, respectively.
650 $aMarker-assisted selection
650 $aSimulation models
650 $aStatistics
650 $aEstatística
653 $aGenomic selection
653 $aRegularized regression
653 $aSeleção genômica
653 $aSNP effects
700 1 $aSILVA, F. F. e
700 1 $aRESENDE, M. D. V. de
700 1 $aCRUZ, C. D.
700 1 $aNASCIMENTO, A. C. C.
700 1 $aVIANA, J. M. S.
700 1 $aAZEVEDO, C. F.
700 1 $aBARROSO, L. M. A.
773 $tGenetics and Molecular Research$gv. 16, n. 1, gmr16019538, 2017.
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Registro original: |
Embrapa Florestas (CNPF) |
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| Registros recuperados : 48 | |
| 3. |  | LOPES, M. T. G.; VIANA, J. M. S.; LOPES, R. Adaptabilidade e estabilidade de híbridos de famílias endogâmicas de milho, obtidos pelo método dos híbridos crípticos. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 36, n. 3, p. 483-91, mar. 2001 Título em inglês: Adaptability and stability patterns in endogamic hybrid maize families, obtained by the cryptic hybrids method.| Biblioteca(s): Embrapa Unidades Centrais. |
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| 5. | | SILVA, H. D.; REGAZZI, A. J.; CRUZ, C. D.; VIANA, J. M. S. Análise de experimentos em látice quadrado com ênfase em componentes de variância. I. Análises individuais. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 34, n. 10, p. 1811-21, out. 1999 Título em inglês: Analysis of experiments in square lattice with emphasis on variance components. i. Individual analysis.| Biblioteca(s): Embrapa Unidades Centrais. |
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| 6. | | REGAZZI, A. J.; SILVA, H. D.; VIANA, J. M. S.; CRUZ, C. D. Analise de experimentos em látice quadrado com ênfase em componentes de variância. II. Análise conjunta. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 34, n. 11, p. 1987-97, nov. 1999 Título em inglês: Analysis of experiments in square lattice with emphasis on variance components: II. Joint analysis.| Biblioteca(s): Embrapa Unidades Centrais. |
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| 13. | | FARIA, V. R.; VIANA, J. M. S.; SOBREIRA, F. M.; SILVA, A. C. e. Seleção recorrente recíproca na obtenção de híbridos interpopulacionais de milho-pipoca. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 43, n. 12, p. 1749-1755, dez. 2008. Título em inglês: Reciprocal recurrent selection to obtain interpopulation hybrids of popcorn.| Biblioteca(s): Embrapa Unidades Centrais. |
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| 14. | | CERESINO, E. B.; MINIM, V. P. R.; QUEIROZ, V. A. V.; PACHECO, C. A. P.; VIANA, J. M. S. Aceitabilidade de diferentes cultivares de milho de pipoca. In: CONGRESSO BRASILEIRO DE CIÊNCIA E TECNOLOGIA DOS ALIMENTOS, 21.; SEMINÁRIO LATINOAMERICANO E DO CARIBE DE CIÊNCIA E TECNOLOGIA DE ALIMENTOS, 15., 2008, Belo Horizonte. Anais... Belo Horizonte: Sociedade Brasileira de Ciência e Tecnologia de Alimentos, 2008. 3 p. 1 CD-ROM.| Tipo: Artigo em Anais de Congresso / Nota Técnica |
| Biblioteca(s): Embrapa Tabuleiros Costeiros. |
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| 15. | | CERESINO, E. B.; MINIM, V. P. R.; QUEIROZ, V. A. V.; PACHECO, C. A. P.; VIANA, J. M. S. Aceitabilidade de diferentes cultivares de milho de pipoca. In: CONGRESSO BRASILEIRO DE CIÊNCIA E TECNOLOGIA DOS ALIMENTOS, 21.; SEMINÁRIO LATINOAMERICANO E DO CARIBE DE CIÊNCIA E TECNOLOGIA DE ALIMENTOS, 15., 2008, Belo Horizonte. Anais... Belo Horizonte: Sociedade Brasileira de Ciência e Tecnologia de Alimentos, 2008. 1 CD-ROM.| Tipo: Artigo em Anais de Congresso / Nota Técnica |
| Biblioteca(s): Embrapa Milho e Sorgo. |
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| 16. | | FARIA, V. R.; VIANA, J. M. S.; MUNDIM, G. B.; SILVA, A. da C. e; CÂMARA, T. M. M. Adaptabilidade e estabilidade de populações de milho-pipoca relacionadas por ciclos de seleção. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 45, n. 12, p. 1396-1403, dez. 2010 Título em inglês: Adaptability and stability of popcorn populations related through selection cycles.| Biblioteca(s): Embrapa Unidades Centrais. |
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| 20. | | BONOMO, P.; CRUZ, C. D.; VIANA, J. M. S.; PEREIRA, A. A.; OLIVEIRA, V. R.; CARNEIRO, P. C. S. Avaliação de progênies obtidas de cruzamentos de descendentes do híbrido de timor com as Cultivares Catuaí Vermelho e Catuaí Amarelo. Bragantia, Campinas, v. 63, n. 2, p. 207-219, 2004.| Biblioteca(s): Embrapa Hortaliças. |
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| Registros recuperados : 48 | |
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| Nenhum registro encontrado para a expressão de busca informada. |
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