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| 2. |  | RODRÍGUEZ, J.D.; PERIPOLLI, E.; LONDOÑO-GIL, M.; ESPIGOLAN, R.; LÔBO, R. B.; LÓPEZ-CORREA, R.; AGUILAR, I.; BALDI, F. Effect of minor allele frequency and density of single nucleotide polymorphism marker arrays on imputation performance and prediction ability using the single-step genomic Best Linear Unbiased Prediction in a simulated beef cattle population. Research paper. Animal Production Science. 2023, volume 63, issue 9, p. 844-852. https://doi.org/10.1071/AN21581 Article history: Submitted 1 December 2021, Accepted 1 March 2023, Published 4 April 2023. -- Correspondence to: Juan Diego Rodríguez,
Universidade Estadual Paulista (Unesp), Faculdade de Ciências Agrarias e Veterinárias, Departamento...| Biblioteca(s): INIA Las Brujas. |
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| 3. | | RODRÍGUEZ NEIRA, J.D.; PERIPOLLI, E.; DE NEGREIROS M.P.M.; ESPIGOLAN, R.; LÓPEZ-CORREA R.; AGUILAR, I.; LOBO R.B.; BALDI, F. Prediction ability for growth and maternal traits using SNP arrays based on different marker densities in Nellore cattle using the ssGBLUP. Journal of Applied Genetics, 2022, Volume 63, Issue 2, pages 389-400. doi: https://doi.org/10.1007/s13353-022-00685-0 Article history: Received 26 September 2021; Revised 25 January 2022; Accepted 2 February 2022.
Corresponding author: Rodriguez Neira, J.D.; Departamento de Zootecnia, Faculdade de Ciências Agrarias e Veterinárias, Universidade...| Biblioteca(s): INIA Las Brujas. |
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 | Acceso al texto completo restringido a Biblioteca INIA Las Brujas. Por información adicional contacte bibliolb@inia.org.uy. |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
28/07/2023 |
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Actualizado : |
28/07/2023 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
Internacional - -- |
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Autor : |
RODRÍGUEZ, J.D.; PERIPOLLI, E.; LONDOÑO-GIL, M.; ESPIGOLAN, R.; LÔBO, R. B.; LÓPEZ-CORREA, R.; AGUILAR, I.; BALDI, F. |
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Afiliación : |
JUAN DIEGO RODRÍGUEZ, Faculdade de Ciências Agrarias e Veterinárias, Departamento de Zootecnia, Universidade Estadual Paulista (Unesp), Jaboticabal, 14884-900, Brazil.; ELISA PERIPOLLI, Faculdade de Ciências Agrarias e Veterinárias, Departamento de Zootecnia, Universidade Estadual Paulista (Unesp), Jaboticabal, 14884-900, Brazil; MARISOL LONDOÑO-GIL, Faculdade de Ciências Agrarias e Veterinárias, Departamento de Zootecnia, Universidade Estadual Paulista (Unesp), Jaboticabal, 14884-900, Brazil; RAFAEL ESPIGOLAN, Faculdade de Zootecnia e Engenharia de Alimentos, Departamento de Medicina Veterinária, Universidade de São Paulo (Usp), Pirassununga, 13535-900, Brazil.; RAYSILDO BARBOSA LÔBO, Associação Nacional de Criadores e Pesquisadores, Ribeirão Preto, Brazil; RODRIGO LÓPEZ-CORREA, Facultad de Veterinaria, Departamento de Genética y Mejoramiento Animal, Universidad de la República, Montevideo, Uruguay; IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; FERNANDO BALDI, Faculdade de Ciências Agrarias e Veterinárias, Departamento de Zootecnia, Universidade Estadual Paulista (Unesp), Jaboticabal, 14884-900, Brazil. |
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Título : |
Effect of minor allele frequency and density of single nucleotide polymorphism marker arrays on imputation performance and prediction ability using the single-step genomic Best Linear Unbiased Prediction in a simulated beef cattle population. |
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Complemento del título : |
Research paper. |
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Fecha de publicación : |
2023 |
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Fuente / Imprenta : |
Animal Production Science. 2023, volume 63, issue 9, p. 844-852. https://doi.org/10.1071/AN21581 |
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ISSN : |
1836-0939; eISSN: 1836-5787. |
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DOI : |
10.1071/AN21581 |
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Idioma : |
Inglés |
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Notas : |
Article history: Submitted 1 December 2021, Accepted 1 March 2023, Published 4 April 2023. -- Correspondence to: Juan Diego Rodríguez,
Universidade Estadual Paulista (Unesp), Faculdade de Ciências Agrarias e Veterinárias, Departamento de Zootecnia, Jaboticabal, 14884-900, Brazil. Email: juan.diego@unesp.br -- Handling Editor: Kim Bunter. -- |
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Contenido : |
Context: In beef cattle populations, there is little evidence regarding the minimum number of genetic markers needed to obtain reliable genomic prediction and imputed genotypes.
Aims: This study aimed to evaluate the impact of single nucleotide polymorphism (SNP) marker density and minor allele frequency (MAF), on genomic predictions and imputation performance for high and low heritability traits using the single-step genomic Best Linear Unbiased Prediction methodology (ssGBLUP) in a simulated beef cattle population.
© 2023 The Author(s) (or their employer(s)). Published by CSIRO Publishing |
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Palabras claves : |
Bias; Bovine; Customised SNP arrays; Genomic selection; Imputation accuracy; Inflation; MAF; Simulation. |
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Asunto categoría : |
L10 Genética y mejoramiento animal |
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Marc : |
LEADER 02068naa a2200337 a 4500
001 1064277
005 2023-07-28
008 2023 bl uuuu u00u1 u #d
022 $a1836-0939; eISSN: 1836-5787.
024 7 $a10.1071/AN21581$2DOI
100 1 $aRODRÍGUEZ, J.D.
245 $aEffect of minor allele frequency and density of single nucleotide polymorphism marker arrays on imputation performance and prediction ability using the single-step genomic Best Linear Unbiased Prediction in a simulated beef cattle population.$h[electronic resource]
260 $c2023
500 $aArticle history: Submitted 1 December 2021, Accepted 1 March 2023, Published 4 April 2023. -- Correspondence to: Juan Diego Rodríguez, Universidade Estadual Paulista (Unesp), Faculdade de Ciências Agrarias e Veterinárias, Departamento de Zootecnia, Jaboticabal, 14884-900, Brazil. Email: juan.diego@unesp.br -- Handling Editor: Kim Bunter. --
520 $aContext: In beef cattle populations, there is little evidence regarding the minimum number of genetic markers needed to obtain reliable genomic prediction and imputed genotypes. Aims: This study aimed to evaluate the impact of single nucleotide polymorphism (SNP) marker density and minor allele frequency (MAF), on genomic predictions and imputation performance for high and low heritability traits using the single-step genomic Best Linear Unbiased Prediction methodology (ssGBLUP) in a simulated beef cattle population. © 2023 The Author(s) (or their employer(s)). Published by CSIRO Publishing
653 $aBias
653 $aBovine
653 $aCustomised SNP arrays
653 $aGenomic selection
653 $aImputation accuracy
653 $aInflation
653 $aMAF
653 $aSimulation
700 1 $aPERIPOLLI, E.
700 1 $aLONDOÑO-GIL, M.
700 1 $aESPIGOLAN, R.
700 1 $aLÔBO, R. B.
700 1 $aLÓPEZ-CORREA, R.
700 1 $aAGUILAR, I.
700 1 $aBALDI, F.
773 $tAnimal Production Science. 2023, volume 63, issue 9, p. 844-852. https://doi.org/10.1071/AN21581
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