Fecha/hora: 03/06/2024 08:41:49

Biblioteca(s): 	INIA Las Brujas.	
Fecha corriente: 	14/06/2022	
Fecha de la última actualización: 	14/06/2022	
Autoria: 	GARCÍA, A.; AGUILAR, I.; LEGARRA, A.; MILLER, S.; TSURUTA, S.; MISZTAL, I.; LOURENCO, D.	
Afiliación: 	ANDRÉ GARCÍA, University of Georgia; IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ANDRÉS LEGARRA, UMR GenPhySE, INRA; STEPHEN P. MILLER, Angus Genetics Inc; SHOGO TSURUTA, University of Georgia; IGNACY MISZTAL, University of Georgia; DANIELA LOURENCO, University of Georgia.	
Título: 	Accuracy of indirect predictions for large datasets based on prediction error covariance of SNP effects from single-step GBLUP. [abstract 22].	
Complemento del título: 	Issue Section: Animal Breeding and Genetics.	
Año de publicación: 	2020	
Fuente/Imprenta: 	Journal of Animal Science, 2020, Volume 98, Issue Supplement 4, Pages 6-7. doi: https://doi.org/10.1093/jas/skaa278.012	
ISSN: 	1525-3163	
DOI: 	10.1093/jas/skaa278.012	
Idioma: 	Inglés	
Notas: 	Article history: 30 November 2020.
ASAS Annual 2020 Meeting Abstracts.	
Contenido: 	ABSTRACT - With an ever-increasing number of genotyped animals, there is a question of whether to include all genotypes into single-step GBLUP (ssGBLUP) evaluations or to include only genotyped animals with phenotypes and use indirect predictions (IP) for the remaining young genotyped animals. Under ssGBLUP, SNP effects can be backsolved from GEBV, and IP can be calculated as the sum of SNP effects weighted by the gene content.	
Palabras-Clave: 	Interim evaluations; SNP PEC.	
Categoría del tema: 	L10 Genética y mejoramiento animal	
Registro original: 	INIA Las Brujas (LB)	
Ejemplares: 	LB - (103100-1) - PXI - PC - DD - Jr.Animal Science/Supplement 4/2020 -  -  - DIS