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| Registros recuperados : 4 | |
| 3. |  | LEGARRA, A.; CHRISTENSEN, O. F.; VITEZICA, Z. G.; AGUILAR, I.; MISZTAL, I. Across-breeds ancestral relationships and metafounders for genomic evaluation. Volume Genetic Improvement Programs: Selection using molecular information, 075. In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 10., Vancouver, BC, Canada, August 17-22, 2014. p.075. Acknowledgements: This project has been financed by X-Gen and GenSSeq actions from SelGen metaprogram (INRA). We are grateful to the genotoul bioinformatics platform Toulouse Midi-Pyrenees for providing computing resources.| Biblioteca(s): INIA Las Brujas. |
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| 4. | | MACEDO, F.; CHRISTENSEN, O. F.; ASTRUC, J.M.; AGUILAR, I.; MASUDA, Y.; LEGARRA, A. Bias and accuracy of dairy sheep evaluations using BLUP and SSGBLUP with metafounders and unknown parent groups. Genetics, Selection, Evolution : GSE, 12 August 2020, Volume 52, Issue 1, Page 47. OPEN ACCESS. DOI: https://doi.org/10.1186/s12711-020-00567-1 Article history: Received 03 March 2020; Accepted 04 August 2020; Published 12 August 2020.| 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 : |
10/09/2014 |
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Actualizado : |
11/11/2019 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
A - 2 |
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Autor : |
LEGARRA, A.; CHRISTENSEN, O.F.; AGUILAR, I.; MISZTAL, I. |
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Afiliación : |
IGNACIO AGUILAR GARCIA, Instituto Nacional de Investigación Agropecuaria (INIA), Uruguay. |
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Título : |
Single Step, a general approach for genomic selection. |
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Fecha de publicación : |
2014 |
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Fuente / Imprenta : |
Livestock Science, 2014, v.166, no.1, p.54-65. |
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ISSN : |
1871-1413 |
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DOI : |
10.1016/j.livsci.2014.04.029 |
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Idioma : |
Inglés |
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Notas : |
Article history: Available online 2 May 2014. |
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Contenido : |
ABSTRACT.
Genomic evaluation methods assume that the reference population is genotyped and phenotyped. This is most often false and the generation of pseudo-phenotypes is uncertain and inaccurate. However, markers obey transmission rules and therefore the covariances of marker genotypes across individuals can be modelled using pedigree relationships. Based on this, an extension of the genomic relationship matrix can be constructed in which genomic relationships are propagated to all individuals, resulting in a combined relationship matrix, which can be used in a BLUP procedure called the Single Step Genomic BLUP. This procedure provides so far the most comprehensive option for genomic evaluation. Several extensions, options and details are described: compatibility of genomic and pedigree relationships, Bayesian regressions, multiple trait models, computational aspects, etc. Many details scattered through a series of papers are put together into this paper.
© 2014 Elsevier B.V. |
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Palabras claves : |
BLUP; GENETIC EVALUATION; GENOMIC EVALUATION; MARKER GENOTYPES; RELATIONSHIP. |
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Thesagro : |
BLUP; EVALUACIÓN GENÉTICA; GENOTIPOS; MARCADORES GENÉTICOS. |
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Asunto categoría : |
L10 Genética y mejoramiento animal |
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Marc : |
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100 1 $aLEGARRA, A.
245 $aSingle Step, a general approach for genomic selection.$h[electronic resource]
260 $c2014
500 $aArticle history: Available online 2 May 2014.
520 $aABSTRACT. Genomic evaluation methods assume that the reference population is genotyped and phenotyped. This is most often false and the generation of pseudo-phenotypes is uncertain and inaccurate. However, markers obey transmission rules and therefore the covariances of marker genotypes across individuals can be modelled using pedigree relationships. Based on this, an extension of the genomic relationship matrix can be constructed in which genomic relationships are propagated to all individuals, resulting in a combined relationship matrix, which can be used in a BLUP procedure called the Single Step Genomic BLUP. This procedure provides so far the most comprehensive option for genomic evaluation. Several extensions, options and details are described: compatibility of genomic and pedigree relationships, Bayesian regressions, multiple trait models, computational aspects, etc. Many details scattered through a series of papers are put together into this paper. © 2014 Elsevier B.V.
650 $aBLUP
650 $aEVALUACIÓN GENÉTICA
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650 $aMARCADORES GENÉTICOS
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653 $aRELATIONSHIP
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700 1 $aAGUILAR, I.
700 1 $aMISZTAL, I.
773 $tLivestock Science, 2014$gv.166, no.1, p.54-65.
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