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Registros recuperados : 45 | |
4. | | MASUDA, Y.; AGUILAR, I.; TSURUTA, S.; MISZTAL, I. Acceleration of computations in AI REML for single-step GBLUP models. Volume Methods and Tools: Statistical methods - linear and nonlinear models (Posters), 703. In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 10., Vancouver, BC, Canada, August 17-22, 2014. p.703.Biblioteca(s): INIA Las Brujas. |
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6. | | AGUILAR, I.; MISZTAL, I.; LEGARRA, A.; TSURUTA, S. Efficient computations of genomic relationship matrix and other matrices used in the single-step evaluation. Volume Methods and tools: Software and bioinformatics - Lecture Sessions, 0768. In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 9., Leipzig, Germany, August 1-6, 2010. p. 0768. Acknowledgments: This study was partially funded by the Holstein Association USA Inc. and by AFRI grants 2009-65205-05665 and 2010-65205-20366 from the USDA NIFA Animal Genome Program. The authors thank P.M. VanRaden from Animal...Biblioteca(s): INIA Las Brujas. |
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8. | | TSURUTA, S.; MISZTAL, I.; AGUILAR, I.; LAWLOR, T. J. Genome wide association study on cow mortality in three US regions. Volume Species Breeding: Dairy cattle (Posters), 805. In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 10., Vancouver, BC, Canada, August 17-22, 2014. p.805.Biblioteca(s): INIA Las Brujas. |
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9. | | TSURUTA, S.; MISZTAL, I.; AGUILAR, I.; LAWLOR, T.J. Multiple-trait genomic evaluation of linear type traits using genomic and phenotypic data in US Holsteins. Journal of Dairy Science, 2011, v.94, no.8, p.4198-4204. OPEN ACCESS. Article history: Received February 9, 2011. / Accepted April 8, 2011.Biblioteca(s): INIA Las Brujas. |
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10. | | AGUILAR, I.; MISZTAL, I.; TSURUTA, S.; LEGARRA, A.; WANG, H. PREGSF90 - POSTGSF90: Computational tools for the implementation of single-step genomic selection and genome-wide association with ungenotyped individuals in BLUPF90 programs. Volume Methods and Tools: Statistical and genomic tools for mapping QTL and genes (Posters), 680. In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 10., Vancouver, BC, Canada, August 17-22, 2014. p.680.Biblioteca(s): INIA Las Brujas. |
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11. | | MASUDA, Y.; AGUILAR, I.; TSURUTA, S.; MISZTAL, I. Technical note: Acceleration of sparse operations for average-information REML analyses with supernodal methods and sparse-storage refinements. Journal of Animal Science, 2015, v. 93, p. 4670 - 4674. Published October 9, 2015 Article history: Received June 8, 2015.; Accepted August 7, 2015.
1. We acknowledge the work by François Guillaume in programming a hash function. We greatly appreciate the work of the two anonymous reviewers.
2. The AIREMLF90 program...Biblioteca(s): INIA Las Brujas. |
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13. | | LOURENCO, D; MISZTAL, I.; TSURUTA, S.; AGUILAR, I.; LAWLOR, T. J.; WELLER, J. I. Are evaluations on young genotyped dairy bulls benefiting from the past generations? [conference paper]. Volume Species Breeding: Dairy cattle, 297. In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 10., Vancouver, BC, Canada, August 17-22, 2014. p.297.Biblioteca(s): INIA Las Brujas. |
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14. | | GARCÍA, A.; AGUILAR, I.; LEGARRA, A.; MILLER, S.; TSURUTA, S.; MISZTAL, I.; LOURENCO, D. Accuracy of indirect predictions for large datasets based on prediction error covariance of SNP effects from single-step GBLUP. [abstract 22]. Issue Section: Animal Breeding and Genetics. Journal of Animal Science, 2020, Volume 98, Issue Supplement 4, Pages 6-7. doi: https://doi.org/10.1093/jas/skaa278.012 Article history: 30 November 2020.
ASAS Annual 2020 Meeting Abstracts.Biblioteca(s): INIA Las Brujas. |
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15. | | AGUILAR, I.; TSURUTA, S.; MASUDA, Y.; LOURENCO, D.A.L.; LEGARRA, A.; MISZTAL, I. BLUPF90 suite of programs for animal breeding with focus on genomics. Volume Methods and Tools - Software, p. 751. In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 11., Aotea Centre Auckland, New Zealand: WCGALP, ICAR, 11-16 feb 2018. 6 p.Biblioteca(s): INIA Las Brujas. |
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16. | | GARCÍA, A.; AGUILAR, I.; LEGARRA, A.; TSURUTA, S.; MISZTAL, I.; LOURENCO, D. Correction: Theoretical accuracy for indirect predictions based on SNP effects from single-step GBLUP (Genetics, selection, evolution : GSE (2022) 54:1 (66)). Genetics, Selection, Evolution : GSE, 2023, Volume 55, Issue 1, Pages 26. OPEN ACCESS. https://doi.org/10.1186/s12711-023-00799-x Article history: Published online 17 April 2023. -- Document: Erratum - Gold Open Access. -- The original article can be found online at https://doi.org/10.1186/s12711-022-00752-4Biblioteca(s): INIA Las Brujas. |
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17. | | LOURENÇO, D. A. L.; MISZTAL, I.; TSURUTA, S.; FRAGOMENI, B.; AGUILAR, I.; MASUDA, Y.; MOSER, D. Direct and indirect genomic evaluations in beef cattle. Interbull Bulletin, 2015, v. 49, p.80 - 84.Biblioteca(s): INIA Las Brujas. |
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18. | | AGUILAR, I.; MISZTAL, I.; JOHNSON, D.L.; LEGARRA, A.; TSURUTA, S.; LAWLOR, T.J. Hot topic: A unified approach to utilize phenotypic, full pedigree, and genomic information for genetic evaluation of Holstein final score. Journal of Dairy Science, 2010, v. 93, no. 2, p. 743-752. OPEN ACCESS Article history: Received September 14, 2009 / Accepted November 10, 2009 / Published in issue: February 2010.Biblioteca(s): INIA Las Brujas. |
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19. | | MISZTAL, I.; LOURENCO, D.; TSURUTA, S.; AGUILAR, I.; MASUDA, Y.; BERMANN, M.; CESARANI, A.; LEGARRA, A. How ssGBLUP became suitable for national dairy cattle evaluations. [668]. Part 37 - Bovine dairy - genetic evaluation methods. In: Proceedings of the World Congress on Genetics Applied to Livestock Production (WCGALP), 12., Rotterdam, the Netherlands, 3-8 July 2022. doi: https://doi.org/10.3920/978-90-8686-940-4_668 2757-2760. Article history: Published online: February 9, 2023 -- Corresponding author: I. Misztal, email: ignacy@uga.eduBiblioteca(s): INIA Las Brujas. |
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20. | | TSURUTA, S.; AGUILAR, I.; MISZTAL, I.; LEGARRA, A.; LAWLOR, T. J. Multiple trait genetic evaluation of linear type traits using genomic and phenotypic data in US Holsteins. Volume Genetic improvement programmes: Selection using molecular information - Poster Sessions, 0489. In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 9., Leipzig, Germany, August 1-6, 2010. p. 0489.Biblioteca(s): INIA Las Brujas. |
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Registros recuperados : 45 | |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
Fecha actual : |
24/07/2020 |
Actualizado : |
24/07/2020 |
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
Circulación / Nivel : |
Internacional - -- |
Autor : |
LOURENCO, D.; LEGARRA, A.; TSURUTA, S.; MASUDA, Y.; AGUILAR, I.; MISZTAL, I. |
Afiliación : |
DANIELA LOURENCO, Department of Animal and Dairy Science, University of Georgia, Athens, GA 30602, USA; ANDRÉS LEGARRA, Institut National de la Recherche Agronomique, UMR1388 GenPhySE, 31326 Castanet Tolosan, France; SHOGO TSURUTA, Department of Animal and Dairy Science, University of Georgia, Athens, GA 30602, USA; YUTAKA MASUDA, Department of Animal and Dairy Science, University of Georgia, Athens, GA 30602, USA; IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; IGNACY MISZTAL, Department of Animal and Dairy Science, University of Georgia, Athens, GA 30602, USA. |
Título : |
Single-step genomic evaluations from theory to practice: using snp chips and sequence data in blupf90. |
Fecha de publicación : |
2020 |
Fuente / Imprenta : |
Genes, July 2020. Volume 11, Issue 7, Article number 790, Pages 1-32. Open Access. Doi: https://doi.org/10.3390/genes11070790 |
ISSN : |
2073-4425 |
DOI : |
10.3390/genes11070790 |
Idioma : |
Inglés |
Notas : |
Article history: Received: 19 June 2020 / Revised: 3 July 2020 / Accepted: 6 July 2020 / Published: 14 July 2020.
(This article belongs to the Special Issue Genomic Prediction Methods for Sequencing Data):
https://www.mdpi.com/journal/genes/special_issues/Genomic_Prediction |
Contenido : |
ABSTRACT.
Single-step genomic evaluation became a standard procedure in livestock breeding, and the main reason is the ability to combine all pedigree, phenotypes, and genotypes available into one single evaluation, without the need of post-analysis processing. Therefore, the incorporation of data on genotyped and non-genotyped animals in this method is straightforward. Since 2009, two main implementations of single-step were proposed. One is called single-step genomic best linear unbiased prediction (ssGBLUP) and uses single nucleotide polymorphism (SNP) to construct the genomic relationship matrix; the other is the single-step Bayesian regression (ssBR), which is a marker effect model. Under the same assumptions, both models are equivalent. In this review, we focus solely on ssGBLUP. The implementation of ssGBLUP into the BLUPF90 software suite was done in 2009, and since then, several changes were made to make ssGBLUP flexible to any model, number of traits, number of phenotypes, and number of genotyped animals. Single-step GBLUP from the BLUPF90 software suite has been used for genomic evaluations worldwide. In this review, we will show theoretical developments and numerical examples of ssGBLUP using SNP data from regular chips to sequence data. |
Palabras claves : |
Genome-wide association; Genomic prediction; Genomic selection; SINGLE-STEP GENOMIC BLUP. |
Asunto categoría : |
A50 Investigación agraria |
URL : |
https://www.mdpi.com/2073-4425/11/7/790/pdf
https://www.mdpi.com/2073-4425/11/7/790/review_report
|
Marc : |
LEADER 02392naa a2200265 a 4500 001 1061236 005 2020-07-24 008 2020 bl uuuu u00u1 u #d 022 $a2073-4425 024 7 $a10.3390/genes11070790$2DOI 100 1 $aLOURENCO, D. 245 $aSingle-step genomic evaluations from theory to practice$busing snp chips and sequence data in blupf90.$h[electronic resource] 260 $c2020 500 $aArticle history: Received: 19 June 2020 / Revised: 3 July 2020 / Accepted: 6 July 2020 / Published: 14 July 2020. (This article belongs to the Special Issue Genomic Prediction Methods for Sequencing Data): https://www.mdpi.com/journal/genes/special_issues/Genomic_Prediction 520 $aABSTRACT. Single-step genomic evaluation became a standard procedure in livestock breeding, and the main reason is the ability to combine all pedigree, phenotypes, and genotypes available into one single evaluation, without the need of post-analysis processing. Therefore, the incorporation of data on genotyped and non-genotyped animals in this method is straightforward. Since 2009, two main implementations of single-step were proposed. One is called single-step genomic best linear unbiased prediction (ssGBLUP) and uses single nucleotide polymorphism (SNP) to construct the genomic relationship matrix; the other is the single-step Bayesian regression (ssBR), which is a marker effect model. Under the same assumptions, both models are equivalent. In this review, we focus solely on ssGBLUP. The implementation of ssGBLUP into the BLUPF90 software suite was done in 2009, and since then, several changes were made to make ssGBLUP flexible to any model, number of traits, number of phenotypes, and number of genotyped animals. Single-step GBLUP from the BLUPF90 software suite has been used for genomic evaluations worldwide. In this review, we will show theoretical developments and numerical examples of ssGBLUP using SNP data from regular chips to sequence data. 653 $aGenome-wide association 653 $aGenomic prediction 653 $aGenomic selection 653 $aSINGLE-STEP GENOMIC BLUP 700 1 $aLEGARRA, A. 700 1 $aTSURUTA, S. 700 1 $aMASUDA, Y. 700 1 $aAGUILAR, I. 700 1 $aMISZTAL, I. 773 $tGenes, July 2020. Volume 11, Issue 7, Article number 790, Pages 1-32. Open Access. Doi: https://doi.org/10.3390/genes11070790
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