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| Registros recuperados : 125 | |
| 21. |  | RENHE, I. R. T.; STRINCHETA, P. C.; SILVA, F. F. e; OLIVEIRA, T. V. de. Obtenção de corante natural azul extraído de frutos de jenipapo. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 44, n. 6, p. 649-652, jun. 2009. Notas científicas.
Título em inglês: Obtention of blue colorant from jenipapo fruit.| Biblioteca(s): Embrapa Agricultura Digital; Embrapa Unidades Centrais. |
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| 22. | | RESENDE, M. D. V. de; AZEVEDO, C. F.; SILVA, F. F. e. Softwares ASREML e R. In: RESENDE, M. D. V. de; SILVA, F. F. e; AZEVEDO, C. F. Estatística matemática, biométrica e computacional: modelos mistos, multivariados, categóricos e generalizados (REML/BLUP), inferência bayesiana, regressão, aleatória, seleção genômica, QTL, GWAS, estatística espacial e temporal, competição, sobrevivência. Viçosa, MG: UFV, 2014. p. 769-807.| Biblioteca(s): Embrapa Florestas. |
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| 26. | | RESENDE, M. D. V. de; AZEVEDO, C. F.; SILVA, F. F. e. Seleção genômica. In: RESENDE, M. D. V. de; SILVA, F. F. e; AZEVEDO, C. F. Estatística matemática, biométrica e computacional: modelos mistos, multivariados, categóricos e generalizados (REML/BLUP), inferência Bayesiana, regressão, aleatória, seleção genômica, QTL, GWAS, estatística espacial e temporal, competição, sobrevivência. Viçosa, MG: UFV, 2014. p. 627-768.| Biblioteca(s): Embrapa Florestas. |
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| 32. | | SANTOS, V. S. dos; MARTINS FILHO, S.; ALVES, R. M.; RESENDE, M. D. V. de; SILVA, F. F. e. Genetic divergence among cupuaçu accessions by multiscale bootstrap resampling. Bragantia, Campinas, v. 74, n. 2, p. 169-175, Apr./June 2015.| Biblioteca(s): Embrapa Amazônia Oriental. |
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| 33. | | SANTOS, V. S. dos; MARTINS FILHO, S.; ALVES, R. M.; RESENDE, M. D. V. de; SILVA, F. F. e. Genetic divergence among cupuaçu accessions by multiscale bootstrap resampling. Bragantia, Campinas, v. 74, n. 2, p. 169-175, Apr./June 2015.| Biblioteca(s): Embrapa Florestas. |
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| 36. | | NASCIMENTO, M.; SILVA, F. F. e; SAFADI, T.; NASCIMENTO, A. C. C.; FERREIRA, R. de P.; CRUZ, C. D. Abordagem bayesiana para avaliação da adaptabilidade e estabilidade de genótipos de alfafa. Pesquisa Agropecuária Brasileira, Brasília, v. 46, n. 1, p. 26-32, jan. 2011.| Biblioteca(s): Embrapa Pecuária Sudeste; Embrapa Unidades Centrais. |
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| 37. | | MORAES, W. B.; MAFFIA, L. A.; SANTOS, A. F. dos; SILVA, F. F. E.; FILHO, S. M. Análise bayesiana em modelos de crescimento para comparar estratégias de controle da ferrugem do álamo. In: CONGRESSO BRASILEIRO DE FITOPATOLOGIA, 46.; REUNIÃO BRASILEIRA DE CONTROLE BIOLÓGICO, 11., 2013, Ouro Preto. CBfito sustentável. Ouro Preto: UFV, 2013. 1 CD-ROM. Resumo: 126-1.| Biblioteca(s): Embrapa Florestas. |
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| 40. | | OLIVEIRA, L. T. de; MENEZES, G. R. de O.; SILVA, F. F. e; OLIVEIRA, H. R. de; VENTURA, H. T. Modelos de limiar em regressão aleatória para avaliação genética da probabilidade de prenhez na raça Sindi. In: SIMPÓSIO BRASILEIRO DE MELHORAMENTO ANIMAL, 12., 2017, Ribeirão Preto, SP. Fenômica e outras ômicas na produção animal: Anais... Sertãozinho: Sociedade de Melhoramento Animal/Instituto de Zootecnia, 2017.| Biblioteca(s): Embrapa Gado de Corte. |
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| Registros recuperados : 125 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Café. |
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Data corrente: |
19/01/2022 |
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Data da última atualização: |
19/01/2022 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
LIMA, L. P.; AZEVEDO, C. F.; RESENDE, M. D. V. de; NASCIMENTO, M.; SILVA, F. F. e. |
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Afiliação: |
LEÍSA PIRES LIMA, UFV; CAMILA FERREIRA AZEVEDO, UFV; MARCOS DEON VILELA DE RESENDE, CNPCa; MOYSÉS NASCIMENTO, UFV; FABYANO FONSECA E SILVA, UFV. |
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Título: |
Evaluation of Bayesian methods of genomic association via chromosomic regions using simulated data. |
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Ano de publicação: |
2022 |
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Fonte/Imprenta: |
Scientia Agricola, v. 79, n. 3, p. 1-10, 2022. |
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Idioma: |
Inglês |
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Conteúdo: |
The development of efficient methods for genome-wide association studies (GWAS) between quantitative trait loci (QTL) and genetic values is extremely important to animal and plant breeding programs. Bayesian approaches that aim to select regions of single nucleotide polymorphisms (SNPs) proved to be efficient, indicating genes with important effects. Among the selection criteria for SNPs or regions, selection criterion by percentage of variance can be explained by genomic regions (%var), selection of tag SNPs, and selection based on the window posterior probability of association (WPPA). To also detect potentially associated regions, we proposed measuring posterior probability of the interval PPint), which aims to select regions based on the markers of greatest effects. Therefore, the objective of this work was to evaluate these approaches, in terms of efficiency in selecting and identifying markers or regions located within or close to genes associated with traits. This study also aimed to compare these methodologies with single-marker analyses. To accomplish this, simulated data were used in six scenarios, with SNPs allocated in non?overlapping genomic regions. Considering traits with oligogenic inheritance, WPPA criterion followed by %var and PPint criteria were shown to be superior, presenting higher values of detection power, capturing higher percentages of genetic variance and larger areas. For traits with polygenic inheritance, PPint and WPPA criteria were considered superior. Single?marker analyses identified SNPs associated only in oligogenic inheritance scenarios and was lower than the other criteria. MenosThe development of efficient methods for genome-wide association studies (GWAS) between quantitative trait loci (QTL) and genetic values is extremely important to animal and plant breeding programs. Bayesian approaches that aim to select regions of single nucleotide polymorphisms (SNPs) proved to be efficient, indicating genes with important effects. Among the selection criteria for SNPs or regions, selection criterion by percentage of variance can be explained by genomic regions (%var), selection of tag SNPs, and selection based on the window posterior probability of association (WPPA). To also detect potentially associated regions, we proposed measuring posterior probability of the interval PPint), which aims to select regions based on the markers of greatest effects. Therefore, the objective of this work was to evaluate these approaches, in terms of efficiency in selecting and identifying markers or regions located within or close to genes associated with traits. This study also aimed to compare these methodologies with single-marker analyses. To accomplish this, simulated data were used in six scenarios, with SNPs allocated in non?overlapping genomic regions. Considering traits with oligogenic inheritance, WPPA criterion followed by %var and PPint criteria were shown to be superior, presenting higher values of detection power, capturing higher percentages of genetic variance and larger areas. For traits with polygenic inheritance, PPint and WPPA criteria were considered ... Mostrar Tudo |
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Thesagro: |
Melhoramento Genético Vegetal; Método de Melhoramento. |
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Thesaurus NAL: |
Genetic variance; Genomics; Molecular models; Plant breeding. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/230380/1/evaluation-of-bayesian-methods.pdf
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Marc: |
LEADER 02367naa a2200241 a 4500
001 2139182
005 2022-01-19
008 2022 bl uuuu u00u1 u #d
100 1 $aLIMA, L. P.
245 $aEvaluation of Bayesian methods of genomic association via chromosomic regions using simulated data.$h[electronic resource]
260 $c2022
520 $aThe development of efficient methods for genome-wide association studies (GWAS) between quantitative trait loci (QTL) and genetic values is extremely important to animal and plant breeding programs. Bayesian approaches that aim to select regions of single nucleotide polymorphisms (SNPs) proved to be efficient, indicating genes with important effects. Among the selection criteria for SNPs or regions, selection criterion by percentage of variance can be explained by genomic regions (%var), selection of tag SNPs, and selection based on the window posterior probability of association (WPPA). To also detect potentially associated regions, we proposed measuring posterior probability of the interval PPint), which aims to select regions based on the markers of greatest effects. Therefore, the objective of this work was to evaluate these approaches, in terms of efficiency in selecting and identifying markers or regions located within or close to genes associated with traits. This study also aimed to compare these methodologies with single-marker analyses. To accomplish this, simulated data were used in six scenarios, with SNPs allocated in non?overlapping genomic regions. Considering traits with oligogenic inheritance, WPPA criterion followed by %var and PPint criteria were shown to be superior, presenting higher values of detection power, capturing higher percentages of genetic variance and larger areas. For traits with polygenic inheritance, PPint and WPPA criteria were considered superior. Single?marker analyses identified SNPs associated only in oligogenic inheritance scenarios and was lower than the other criteria.
650 $aGenetic variance
650 $aGenomics
650 $aMolecular models
650 $aPlant breeding
650 $aMelhoramento Genético Vegetal
650 $aMétodo de Melhoramento
700 1 $aAZEVEDO, C. F.
700 1 $aRESENDE, M. D. V. de
700 1 $aNASCIMENTO, M.
700 1 $aSILVA, F. F. e
773 $tScientia Agricola$gv. 79, n. 3, p. 1-10, 2022.
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Embrapa Café (CNPCa) |
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