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| Registros recuperados : 4 | |
| 1. |  | ALVES, C. J.; FREITAS, T. D.; CLEMENTINO, I. J.; OLIVEIRA, A. G. de F.; ARAÚJO NETO, J. O. de; BATISTA, C. de S. A.; LIMA, F. da S. Pesquisa de Leptospira spp. em amostras de sangue e em órgãos do trato Gênito-urinário de ovinos deslanados na região do semi-árido paraibano. In: CONGRESSO PERNAMBUCANO DE MEDICINA VETERINÁRIA, 5.; SEMINÁRIO NORDESTINO DE CAPRINO-OVINOCULTURA, 6., 2003, Recife. Anais... Recife: Sociedade Pernambucana de Medicina Veterinária, 2003. p. 340-341.| Biblioteca(s): Embrapa Caprinos e Ovinos. |
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| 2. | | ALVES, C. J.; FREITAS, T. D.; CLEMENTINO, I. J.; OLIVEIRA, A. G. de F.; ARAÚJO NETO, J. O. de; BATISTA, C. de S. A.; LIMA, F. da S. Tentativa de isolamento de Leptospira spp. a partir de glândulas genitais acessórias de ovinos deslanados na região do semi-árido brasileiro. Parte I. In: CONGRESSO PERNAMBUCANO DE MEDICINA VETERINÁRIA, 5.; SEMINÁRIO NORDESTINO DE CAPRINO-OVINOCULTURA, 6., 2003, Recife. Anais... Recife: Sociedade Pernambucana de Medicina Veterinária, 2003. p. 346-347.| Biblioteca(s): Embrapa Caprinos e Ovinos. |
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| 3. | | GOMES, A. A. de B.; SILVA, M. L. C. R.; LIMA, F. da S.; OLIVEIRA, A. G. de F.; AZEVEDO, S. S. de; BERNARDES, F.; ITO, F. H. Raiva em caprinos e ovinos inoculados experimentalmente com uma amostra de vírus isolada de raposa (Dusicyon vetutus). In: CONGRESSO NORDESTINO DE PRODUÇÃO ANIMAL, 4.; SIMPÓSIO NORDESTINO DE ALIMENTAÇÃO DE RUMINANTES, 10.; SIMPÓSIO DE PRODUÇÃO ANIMAL DO VALE DO SÃO FRANCISCO, 1., 2006, Petrolina. Anais... Petrolina: Sociedade Nordestina de Produção Animal; Embrapa Semi-Arido, 2006. Seção Sanidade animal..5 f. 1 CD-ROM.| Biblioteca(s): Embrapa Caprinos e Ovinos. |
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| 4. | | GOMES, A. A. de B.; BERNARDI, F.; OLIVEIRA, A. G. de F.; ITO, F. H.; MAIORKA, P. C.; SOARES, R. M. S.; HEINEMANN, M. B.; CORTEZ, A.; RICHTZENHAIN, L. J. Raiva experimental em caprinos e ovinos inoculados com uma amostra de vírus isolada de raposa (Dusicyon vetulus). Ciência Veterinária nos Trópicos, Recife, v. 8, n. 1/3, p. 24-34, jan./dez., 2005.| Biblioteca(s): Embrapa Caprinos e Ovinos. |
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| Registros recuperados : 4 | |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Gado de Leite. Para informações adicionais entre em contato com cnpgl.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Gado de Leite. |
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Data corrente: |
01/12/2014 |
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Data da última atualização: |
05/02/2024 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 2 |
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Autoria: |
BOISON, S. A.; NEVES, H. H. R.; O'BRIEN, A. M. P.; UTSUNOMIYA, Y. T.; CARVALHEIRO, R.; SILVA, M. V. G. B.; SÖLKNER, J.; GARCIA, J. F. |
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Afiliação: |
S.A. BOISON, Univ Nat Resources & Life Sci. BOKU; H.H.R. NEVES, UNESP; A.M. PÉREZ O?BRIEN, Univ Nat Resources & Life Sci. BOKU; Y.T. UTSUNOMIYA, UNESP; R. CARVALHEIRO, UNESP; MARCOS VINICIUS GUALBERTO B SILVA, CNPGL; J. SÖLKNER, Univ Nat Resources & Life Sci. BOKU; J. F. GARCIA, UNESP. |
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Título: |
Imputation of non-genotyped individuals using genotyped progeny in Nellore, a Bos indicus cattle breed. |
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Ano de publicação: |
2014 |
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Fonte/Imprenta: |
Livestock Science, v. 166, p. 176-189, 2014. |
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DOI: |
https://doi.org/10.1016/j.livsci.2014.05.033 |
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Idioma: |
Inglês |
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Conteúdo: |
This study aimed at imputing non(un)-genotyped sires using a stepwise imputation approach that combines identity by descent (IBD) detection methods with other imputation algorithms. We also studied the effect of using actual or imputed genotypes of non-genotyped sires in estimating genomic relationships. Simulations and real data were used for the analysis. Fifty sire families were simulated and 23 sire families were derived from 995 Brazilian Nellore cattle genotyped with Illumina® Bovine HD (777,962 SNPs) SNP Chip. Un-genotyped sires were imputed using genotype information from progeny (5 or 10); progeny and grand offspring; a combination of progeny, mates of genotyped progeny and grand offspring; and the entire genotyped population. Stepwise imputation was done with an IBD detection method that uses simple inheritance rules (MERLIN) as a first step and subsequently with FImpute, MaCH or BEAGLE as the second step to infer genotypes that were not imputed unambiguously by MERLIN. The stepwise imputation procedure was compared to an approach that ignores the first step (MERLIN) but uses only prior pedigree information to impute non-genotyped animals. Imputation accuracy was assessed as percent of correctly called genotypes and the correlation between imputed and actual genotypes (in brackets). With real data, imputation accuracy ranged from 81.6% (0.856) to 97.4% (0.981) depending on the amount of genotyped information considered for the first step (MERLIN) and imputation algorithms used for the second step. Greater accuracies of imputing non-genotyped sires were obtained when the stepwise imputation approach was used with 10 genotyped offspring as the first step. The stepwise approach resulted in an increase of 1.2% (5 offsprings) and 4.7% (10 offsprings) in imputation accuracy. MaCH was more accurate in the second step, followed by FImpute then BEAGLE. Similar trends in imputation accuracy were observed for the simulated population. Generally, imputed genotypes were successfully used to estimate genomic relationships among close relatives but considerable bias was observed for true pairwise relationships of zero. In conclusion, high imputation accuracies can be achieved for non-genotyped animals when genotype information of 5 or 10 direct progeny is available for imputation. Performing preliminary IBD analysis and using non-ambiguous genotypes from that analysis in conventional imputation increased the imputation accuracy considerably. MenosThis study aimed at imputing non(un)-genotyped sires using a stepwise imputation approach that combines identity by descent (IBD) detection methods with other imputation algorithms. We also studied the effect of using actual or imputed genotypes of non-genotyped sires in estimating genomic relationships. Simulations and real data were used for the analysis. Fifty sire families were simulated and 23 sire families were derived from 995 Brazilian Nellore cattle genotyped with Illumina® Bovine HD (777,962 SNPs) SNP Chip. Un-genotyped sires were imputed using genotype information from progeny (5 or 10); progeny and grand offspring; a combination of progeny, mates of genotyped progeny and grand offspring; and the entire genotyped population. Stepwise imputation was done with an IBD detection method that uses simple inheritance rules (MERLIN) as a first step and subsequently with FImpute, MaCH or BEAGLE as the second step to infer genotypes that were not imputed unambiguously by MERLIN. The stepwise imputation procedure was compared to an approach that ignores the first step (MERLIN) but uses only prior pedigree information to impute non-genotyped animals. Imputation accuracy was assessed as percent of correctly called genotypes and the correlation between imputed and actual genotypes (in brackets). With real data, imputation accuracy ranged from 81.6% (0.856) to 97.4% (0.981) depending on the amount of genotyped information considered for the first step (MERLIN) and imputation alg... Mostrar Tudo |
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Palavras-Chave: |
FImpute; Imputation; MaCH; MERLIN; Non(un)-genotyped. |
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Thesaurus NAL: |
Beagle. |
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Categoria do assunto: |
G Melhoramento Genético |
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Marc: |
LEADER 03319naa a2200289 a 4500
001 2001135
005 2024-02-05
008 2014 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1016/j.livsci.2014.05.033$2DOI
100 1 $aBOISON, S. A.
245 $aImputation of non-genotyped individuals using genotyped progeny in Nellore, a Bos indicus cattle breed.$h[electronic resource]
260 $c2014
520 $aThis study aimed at imputing non(un)-genotyped sires using a stepwise imputation approach that combines identity by descent (IBD) detection methods with other imputation algorithms. We also studied the effect of using actual or imputed genotypes of non-genotyped sires in estimating genomic relationships. Simulations and real data were used for the analysis. Fifty sire families were simulated and 23 sire families were derived from 995 Brazilian Nellore cattle genotyped with Illumina® Bovine HD (777,962 SNPs) SNP Chip. Un-genotyped sires were imputed using genotype information from progeny (5 or 10); progeny and grand offspring; a combination of progeny, mates of genotyped progeny and grand offspring; and the entire genotyped population. Stepwise imputation was done with an IBD detection method that uses simple inheritance rules (MERLIN) as a first step and subsequently with FImpute, MaCH or BEAGLE as the second step to infer genotypes that were not imputed unambiguously by MERLIN. The stepwise imputation procedure was compared to an approach that ignores the first step (MERLIN) but uses only prior pedigree information to impute non-genotyped animals. Imputation accuracy was assessed as percent of correctly called genotypes and the correlation between imputed and actual genotypes (in brackets). With real data, imputation accuracy ranged from 81.6% (0.856) to 97.4% (0.981) depending on the amount of genotyped information considered for the first step (MERLIN) and imputation algorithms used for the second step. Greater accuracies of imputing non-genotyped sires were obtained when the stepwise imputation approach was used with 10 genotyped offspring as the first step. The stepwise approach resulted in an increase of 1.2% (5 offsprings) and 4.7% (10 offsprings) in imputation accuracy. MaCH was more accurate in the second step, followed by FImpute then BEAGLE. Similar trends in imputation accuracy were observed for the simulated population. Generally, imputed genotypes were successfully used to estimate genomic relationships among close relatives but considerable bias was observed for true pairwise relationships of zero. In conclusion, high imputation accuracies can be achieved for non-genotyped animals when genotype information of 5 or 10 direct progeny is available for imputation. Performing preliminary IBD analysis and using non-ambiguous genotypes from that analysis in conventional imputation increased the imputation accuracy considerably.
650 $aBeagle
653 $aFImpute
653 $aImputation
653 $aMaCH
653 $aMERLIN
653 $aNon(un)-genotyped
700 1 $aNEVES, H. H. R.
700 1 $aO'BRIEN, A. M. P.
700 1 $aUTSUNOMIYA, Y. T.
700 1 $aCARVALHEIRO, R.
700 1 $aSILVA, M. V. G. B.
700 1 $aSÖLKNER, J.
700 1 $aGARCIA, J. F.
773 $tLivestock Science$gv. 166, p. 176-189, 2014.
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