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Registros recuperados : 22 | |
7. | | RESENDE JUNIOR, M. F. R.; ALVES, A. A.; BARRERA SÁNCHES, C. F.; RESENDE, M. D. V. de; CRUZ, C. D. Seleção genômica ampla. In: CRUZ, C. D.; SALGADO, C. C.; BHERING, L. L. (Ed.). Genômica aplicada. Viçosa, MG: Suprema, 2013. p. 375-424. Biblioteca(s): Embrapa Agroenergia; Embrapa Florestas. |
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8. | | RESENDE JUNIOR, M. F. R.; MUÑOZ, P.; ACOSTA, J. J.; PETER, G. F.; DAVIS, J. M.; GRATTAPAGLIA, D.; RESENDE, M. D. V. de; KIRST, M. Accelerating the domestication of trees using genomic selection: accuracy of prediction models across ages and environments. New Phytologist, v. 193, p. 617-624, 2012. Biblioteca(s): Embrapa Florestas; Embrapa Recursos Genéticos e Biotecnologia. |
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10. | | AZEVEDO, C. F.; RESENDE, M. D. V. de; SILVA, F. F.; VIANA, J. M. S.; VALENTE, M. S. F.; RESENDE JUNIOR, M. F. R.; OLIVEIRA, E. J. de. New accuracy estimators for genomic selection with application in a cassava (Manihot esculenta) breeding program. Genetics and Molecular Research, v. 15, n. 4, gmr.15048838, Oct. 2016. Biblioteca(s): Embrapa Florestas; Embrapa Mandioca e Fruticultura. |
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11. | | RESENDE, M. D. V. de; RESENDE JUNIOR, M. F. R.; AGUIAR, A. M.; ABAD, J. I. M.; MISSIAGGIA, A. A.; SANSALONI, C. P.; PETROLI, C. D.; GRATTAPAGLIA, D. Computação da Seleção Genômica Ampla (GWS). Colombo: Embrapa Florestas, 2010. CD-ROM. (Embrapa Florestas. Documentos, 210). Biblioteca(s): Embrapa Florestas. |
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12. | | ALMEIDA FILHO, J. E. de; GUIMARÃES, J. F. R.; SILVA, F. F. e; RESENDE, M. D. V. de; MUÑOZ, P.; KIRST, M.; RESENDE JUNIOR, M. F. R. The contribution of dominance to phenotype prediction in a pine breeding and simulated population. Heredity, v. 117, p. 33-41, July 2016. Biblioteca(s): Embrapa Florestas. |
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13. | | MÜLLER, B. S. F.; NEVES, L. G.; RESENDE JÚNIOR, M. F. R.; MUÑOZ, P. R.; KIRST, M.; SANTOS, P. E. T. dos; PALUDZYSZYN FILHO, E.; GRATTAPAGLIA, D. Genomic selection for growth traits in Eucalyptus benthamii and E. pellita populations using a genome-wide Eucalyptus 60K SNPs chip. In: IUFRO TREE BIOTECHNOLOGY CONFERENCE, 2015, Florence. Forests: the importance to the planet and society. [S.l.]: IBBR: ICCOM, 2015. Pen-drive. Biblioteca(s): Embrapa Florestas. |
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14. | | AZEVEDO, C. F.; RESENDE, M. D. V. de; SILVA, F. F. e; VIANA, J. M. S.; VALENTE, M. S. F.; RESENDE JUNIOR, M. F. R.; MUÑOZ, P. Ridge, Lasso and Bayesian additive dominance genomic models. BMC Genetics, v. 16, art. 105, Aug. 2015. 13 p. Biblioteca(s): Embrapa Florestas. |
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15. | | MUÑOZ, P. R.; RESENDE JUNIOR, M. F. R.; GEZAN, S. A.; RESENDE, M. D. V. de; CAMPOS, G. de los; KIRST, M.; HUBER, D.; PETER, G. F. Unraveling additive from nonadditive effects using genomic relationship matrices. Genetics, v. 198, p. 1759-1768, Dec. 2014. Biblioteca(s): Embrapa Florestas. |
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16. | | RESENDE JUNIOR, M. F. R.; MUÑOZ, P.; RESENDE, M. D. V. de; GARRICK, D. J.; FERNANDO, R. L.; DAVIS, J. M.; JOKELA, E. J.; MARTIN, T. A.; PETER, G. F.; KIRST, M. Accuracy of genomic selection methods in a standard data set of loblolly pine (Pinus taeda L.) Genetics, v. 190, p. 1503-1510, April 2012. Biblioteca(s): Embrapa Florestas. |
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17. | | GRATTAPAGLIA, D.; RESENDE, M. D. V. de; RESENDE JUNIOR, M. F. R.; SANSALONI, C. P.; PETROLI, C. D.; MISSIAGGIA, A. A.; TAKAHASHI, E. K.; ZAMPROGNO, K. C.; KILIAN, A. Breeding by genomic selection: capturing the missing heritability of complex traits in forest trees. In: NEW PHYTOLOGIST SYMPOSIUM, 26., 2011, Nancy. Bioenergy trees. [S.l.]: INRA, 2011. p. 9. Biblioteca(s): Embrapa Florestas. |
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18. | | ALMEIDA FILHO, J. E. de A.; GUIMARÃES, J. F. R.; SILVA, F. F. e; RESENDE, M. D. V. de; MUÑOZ, P.; KIRST, M.; RESENDE JÚNIOR, M. F. R. de. Genomic prediction of additive and non-additive effects using genetic markers and pedigrees. G3: Genes, Genomes, Genetics, v. 9, p. 2739-2748, Aug. 2019. Biblioteca(s): Embrapa Florestas. |
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19. | | MÜLLER, B. S. F.; NEVES, L. G.; ALMEIDA FILHO, J. E. de; RESENDE JUNIOR, M. F. R.; MUÑOZ, P. R.; SANTOS, P. E. T. dos; PALUDZYSZYN FILHO, E.; KIRST, M.; GRATTAPAGLIA, D. Genomic prediction in contrast to a genome-wide association study in explaining heritable variation of complex growth traits in breeding populations of Eucalyptus. BMC Genomics, v. 18, article 524, 2017. 17 p. Biblioteca(s): Embrapa Florestas; Embrapa Recursos Genéticos e Biotecnologia. |
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20. | | MUNOZ, P. R.; RESENDE JUNIOR, M. F. R.; HUBER, D. A.; QUESADA, T.; RESENDE, M. D. V. de; NEALE, D. B.; WEGRZYN, J. L.; KIRST, M.; PETER, G. F. Genomic relationship matrix for correcting pedigree errors in breeding populations: impact on genetic parameters and genomic selection accuracy. Crop Science, v. 54, p. 115-1123, May/June 2014. Biblioteca(s): Embrapa Florestas. |
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Registros recuperados : 22 | |
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Registro Completo
Biblioteca(s): |
Embrapa Florestas; Embrapa Mandioca e Fruticultura. |
Data corrente: |
28/12/2016 |
Data da última atualização: |
03/01/2018 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
A - 1 |
Autoria: |
AZEVEDO, C. F.; RESENDE, M. D. V. de; SILVA, F. F.; VIANA, J. M. S.; VALENTE, M. S. F.; RESENDE JUNIOR, M. F. R.; OLIVEIRA, E. J. de. |
Afiliação: |
C. F. Azevedo, Departamento de Estatística, Universidade Federal de Viçosa; MARCOS DEON VILELA DE RESENDE, CNPF; F. F. Silva, Departamento de Zootecnia, Universidade Federal de Viçosa; J. M. S. Viana, Departamento de Biologia Geral, Universidade Federal de Viçosa; M. S. F. Valente, Departamento de Biologia Geral, Universidade Federal de Viçosa; M. F. R. Resende Junior, RAPID Genomics, Florida; EDER JORGE DE OLIVEIRA, CNPMF. |
Título: |
New accuracy estimators for genomic selection with application in a cassava (Manihot esculenta) breeding program. |
Ano de publicação: |
2016 |
Fonte/Imprenta: |
Genetics and Molecular Research, v. 15, n. 4, gmr.15048838, Oct. 2016. |
DOI: |
10.4238/gmr.15048838 |
Idioma: |
Inglês |
Conteúdo: |
ABSTRACT. Genomic selection is the main force driving applied breeding programs and accuracy is the main measure for evaluating its efficiency. The traditional estimator (TE) of experimental accuracy is not fully adequate. This study proposes and evaluates the performance and efficiency of two new accuracy estimators, called regularized estimator (RE) and hybrid estimator (HE), which were applied to a practical cassava breeding program and also to simulated data. The simulation study considered two individual narrow sense heritability levels and two genetic architectures for traits. TE, RE, and HE were compared under four validation procedures: without validation (WV), independent validation, ten-fold validation through jacknife allowing different markers, and with the same markers selected in each cycle. RE presented accuracies closer to the parametric ones and less biased and more precise ones than TE. HE proved to be very effective in the WV procedure. The estimators were applied to five traits evaluated in a cassava experiment, including 358 clones genotyped for 390 SNPs. Accuracies ranged from 0.67 to 1.12 with TE and from 0.22 to 0.51 with RE. These results indicated that TE overestimated the accuracy and led to one accuracy estimate (1.12) higher than one, which is outside of the parameter space. Use of RE turned the accuracy into the parameter space. Cassava breeding programs can be more realistically implemented using the new estimators proposed in this study, providing less risky practical inferences. MenosABSTRACT. Genomic selection is the main force driving applied breeding programs and accuracy is the main measure for evaluating its efficiency. The traditional estimator (TE) of experimental accuracy is not fully adequate. This study proposes and evaluates the performance and efficiency of two new accuracy estimators, called regularized estimator (RE) and hybrid estimator (HE), which were applied to a practical cassava breeding program and also to simulated data. The simulation study considered two individual narrow sense heritability levels and two genetic architectures for traits. TE, RE, and HE were compared under four validation procedures: without validation (WV), independent validation, ten-fold validation through jacknife allowing different markers, and with the same markers selected in each cycle. RE presented accuracies closer to the parametric ones and less biased and more precise ones than TE. HE proved to be very effective in the WV procedure. The estimators were applied to five traits evaluated in a cassava experiment, including 358 clones genotyped for 390 SNPs. Accuracies ranged from 0.67 to 1.12 with TE and from 0.22 to 0.51 with RE. These results indicated that TE overestimated the accuracy and led to one accuracy estimate (1.12) higher than one, which is outside of the parameter space. Use of RE turned the accuracy into the parameter space. Cassava breeding programs can be more realistically implemented using the new estimators proposed in this study, provi... Mostrar Tudo |
Palavras-Chave: |
Accuracy estimator; Cross-validation; Genomic prediction; Mnadioca; Seleção genômica. |
Thesagro: |
Mandioca; Manihot esculenta; Melhoramento vegetal. |
Thesaurus NAL: |
Cassava; Plant breeding. |
Categoria do assunto: |
G Melhoramento Genético |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/161813/1/2016-M.Deon-GMR-NewAccuracy.pdf
|
Marc: |
LEADER 02532naa a2200325 a 4500 001 2072711 005 2018-01-03 008 2016 bl uuuu u00u1 u #d 024 7 $a10.4238/gmr.15048838$2DOI 100 1 $aAZEVEDO, C. F. 245 $aNew accuracy estimators for genomic selection with application in a cassava (Manihot esculenta) breeding program.$h[electronic resource] 260 $c2016 520 $aABSTRACT. Genomic selection is the main force driving applied breeding programs and accuracy is the main measure for evaluating its efficiency. The traditional estimator (TE) of experimental accuracy is not fully adequate. This study proposes and evaluates the performance and efficiency of two new accuracy estimators, called regularized estimator (RE) and hybrid estimator (HE), which were applied to a practical cassava breeding program and also to simulated data. The simulation study considered two individual narrow sense heritability levels and two genetic architectures for traits. TE, RE, and HE were compared under four validation procedures: without validation (WV), independent validation, ten-fold validation through jacknife allowing different markers, and with the same markers selected in each cycle. RE presented accuracies closer to the parametric ones and less biased and more precise ones than TE. HE proved to be very effective in the WV procedure. The estimators were applied to five traits evaluated in a cassava experiment, including 358 clones genotyped for 390 SNPs. Accuracies ranged from 0.67 to 1.12 with TE and from 0.22 to 0.51 with RE. These results indicated that TE overestimated the accuracy and led to one accuracy estimate (1.12) higher than one, which is outside of the parameter space. Use of RE turned the accuracy into the parameter space. Cassava breeding programs can be more realistically implemented using the new estimators proposed in this study, providing less risky practical inferences. 650 $aCassava 650 $aPlant breeding 650 $aMandioca 650 $aManihot esculenta 650 $aMelhoramento vegetal 653 $aAccuracy estimator 653 $aCross-validation 653 $aGenomic prediction 653 $aMnadioca 653 $aSeleção genômica 700 1 $aRESENDE, M. D. V. de 700 1 $aSILVA, F. F. 700 1 $aVIANA, J. M. S. 700 1 $aVALENTE, M. S. F. 700 1 $aRESENDE JUNIOR, M. F. R. 700 1 $aOLIVEIRA, E. J. de 773 $tGenetics and Molecular Research$gv. 15, n. 4, gmr.15048838, Oct. 2016.
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