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| Registros recuperados : 17 | |
| 1. |  | 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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| 2. | | 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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| 3. | | 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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| 4. | | 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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| 5. | | 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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| 6. | | AGUILAR, I.; LEGARRA, A.; CARDOSO, F.; MASUDA, Y.; LOURENCO, D.; MISZTAL, I. Frequentist p-values for large-scale-single step genome-wide association, with an application to birth weight in American Angus cattle. (Short Communication) Genetics Selection Evolution, 20 June 2019, v. 51, Issue 1, Article number 28. OPEN ACCESS. Article history: Received: 3 January 2019 // Accepted: 27 May 2019 // Published Online: 20 June 2019.
Funding text: This study was partially funded by the American Angus Association (St. Joseph, MO) and by Agriculture and Food Research...| Biblioteca(s): INIA Las Brujas. |
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| 7. | | 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.edu| Biblioteca(s): INIA Las Brujas. |
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| 8. | | LOURENCO, D.; TSURUTA, S.; AGUILAR, I.; MASUDA, Y.; BERMANN, M.; LEGARRA, A.; MISZTAL, I. Recent updates in the BLUPF90 software suite. [366]. Part 19 - Methods and tools: software and computing strategies. 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_366 1530-1533. Article history: Published online: February 9, 2023. -- Corresponding author: D. Lourenco, email: danilino@uga.edu| Biblioteca(s): INIA Las Brujas. |
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| 9. | | LOURENCO, D.; LEGARRA, A.; TSURUTA, S.; MASUDA, Y.; AGUILAR, I.; MISZTAL, I. Single-step genomic evaluations from theory to practice: using snp chips and sequence data in blupf90. Genes, July 2020. Volume 11, Issue 7, Article number 790, Pages 1-32. Open Access. Doi: https://doi.org/10.3390/genes11070790 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):...| Biblioteca(s): INIA Las Brujas. |
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| 10. | | FRAGOMENI, B.O.; LOURENCO, D.A.L.; TSURUTA, S.; MASUDA, Y.; AGUILAR, I.; MISZTAL, I. Use of genomic recursions and algorithm for proven and young animals for single-step genomic BLUP analyses - a simulation study. Journal of Animal Breeding and Genetics, 2015, v.132, no.5, p. 340-345.| Biblioteca(s): INIA Las Brujas. |
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| 11. | | MISZTAL, I.; FRAGOMENI, B.; LOURENÇO, D. A. L.; TSURUTA, S.; MASUDA, Y.; AGUILAR, I.; LEGARRA, A.; LAWLOR, T. J. Efficient inversion of genomic relationship matrix by the Algorithm for Proven and Young (APY). Interbull Bulletin, 2015, v. 49, p. 111-116.| Biblioteca(s): INIA Las Brujas. |
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| 12. | | FRAGOMENI, B.O.; LOURENCO, D.A.L.; TSURUTA, S.; MASUDA, Y.; AGUILAR, I.; LEGARRA, A.; LAWLOR, T.J.; MIZTAL, I. Hot topic: Use of genomic recursions in single-step genomic best linear unbiased predictor (BLUP) with a large number of genotypes. Journal of Dairy Science, 2015, v.98, no.6, p.4090-4094. OPEN ACCESS. Article history: Received November 18, 2014 / Accepted March 13, 2015 / Published online: April 8, 2015.| Biblioteca(s): INIA Las Brujas. |
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| 13. | | MASUDA, Y.; MISZTAL, I.; TSURUTA, S.; LEGARRA, A.; AGUILAR, I.; LOURENCO, D.A.L.; FRAGOMENI, B.O.; LAWLOR, T.J. Implementation of genomic recursions in single-step genomic best linear unbiased predictor for US Holsteins with a large number of genotyped animals. Journal of Dairy Science, 2016, v.99, no.3, p.1968-1974. OPEN ACCESS OPEN ACCESS. Received 19 October 2015, Accepted 1 December 2015, Available online 21 January 2016| Biblioteca(s): INIA Las Brujas. |
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| 14. | | LOURENCO, D.; TSURUTA, S.; FRAGOMENI, B.; MASUDA, Y.; AGUILAR, I.; LEGARRA, A.; MILLER, S.; MOSER, D.; MISZTAL, I. Single-step genomic BLUP for national beef cattle evaluation in US: from initial developments to final implementation. Volume Species - Bovine (beef) 1, 495. In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 11., Aotea Centre Auckland, New Zealand: WCGALP, ICAR, 11-16 feb 2018.| Biblioteca(s): INIA Las Brujas. |
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| 15. | | MASUDA, Y.; MISZTAL, I.; TSURUTA, S.; LOURENÇO, D. A. L.; FRAGOMENI, B.; LEGARRA, A.; AGUILAR, I.; LAWLOR, T. J. Single-step genomic evaluations with 570K genotyped animals in US Holsteins. Interbull Bulletin, 2015, v. 49, p. 85-89.| Biblioteca(s): INIA Las Brujas. |
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| 16. | | MASUDA, Y; MISZTAL, I.; LEGARRA, A.; TSURUTA, S.; LOURENCO, D.A.L.; FRAGOMENI, B.O.; AGUILAR, I. Technical note: Avoiding the direct inversion of the numerator relationship matrix for genotyped animals in single-step genomic best linear unbiased prediction solved with the preconditioned conjugate gradient. Journal of Animal Science, 2017, v. 95(1): 49-52. Article history: Received: July 05, 2016; Accepted: Aug 16, 2016; Published: February 2, 2017.
This research was partially funded by the United States Department of Agriculture?s National Institute of Food and Agriculture (Agriculture and...| Biblioteca(s): INIA Las Brujas. |
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| 17. | | LOURENCO, D. A. L.; TSURUTA, S.; FRAGOMENI, B. O.; MASUDA, Y.; AGUILAR, I.; LEGARRA, A.; BERTRAND, J. K.; AMEN, T. S.; WANG. L.; MOSER, D. W.; MISZTAL, I. Genetic evaluation using single-step genomic best linear unbiased predictor in American Angus.(*) Journal of Animal Science, 2015, v. 93, p. 2653-2662. Published June 25, 2015. OPEN ACCESS. (*) This study was partially funded by the American Angus Association (St. Joseph, MO), Zoetis (Kalamazoo, MI), and Agriculture and Food Research Initiative Competitive Grants no. 2015-67015-22936 from the U.S. Department of Agriculture?s...| Biblioteca(s): INIA Las Brujas. |
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| Registros recuperados : 17 | |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
21/02/2014 |
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Actualizado : |
18/12/2018 |
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Tipo de producción científica : |
Artículos Indexados |
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Autor : |
MISZTAL, I.; FRAGOMENI, B.; LOURENÇO, D. A. L.; TSURUTA, S.; MASUDA, Y.; AGUILAR, I.; LEGARRA, A.; LAWLOR, T. J. |
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Afiliación : |
IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
Efficient inversion of genomic relationship matrix by the Algorithm for Proven and Young (APY). |
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Fecha de publicación : |
2015 |
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Fuente / Imprenta : |
Interbull Bulletin, 2015, v. 49, p. 111-116. |
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Idioma : |
Inglés |
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Contenido : |
ABSTRACT.
The purpose of this study was to evaluate properties of the inverse of the genomic relationship matrix derived with the algorithm for proven and young (APY) and the accuracy of genomic selection in single-step genomic best linear unbiased prediction (ssGBLUP). The APY implements genomic recursions on a subset of genotyped animals. When that subset is small, the cost of APY is approximately linear in memory and computations, effectively removing restrictions on the number of genotypes. Tests involved 10 102 702 final scores from 6 930 618 Holstein cows. A total of 100 000 animals with genotypes were used in the analyses and included 23 174 sires, 27 215 cows and 49 611 young animals. Genomic estimated breeding values (GEBVs) were calculated using ssGBLUP with a regular inverse of the genomic relationship matrix (G) and with G inverse from APY. Many subsets were tested including only sires, only cows and random samples from 2 000 to 20 000 animals. When the number of animals in the subset was ≥15,000, the correlations between GEBV with APY and
GEBV with the regular inverse were ≥0.99. Best convergence rate was achieved with random samples. A theory on APY was derived and is based on the fact that additive effects of animals in the subset are linear functions of the effects of independent chromosome segments (ICSs); the number of segments is a function of the effective population size. Accuracy of GEBV with APY can be slightly superior to that of a regular inverse. The inverse with APY is computed from G, which in turn is derived from single nucleotide polymorphism (SNP) BLUP and indirectly from BayesB or other SNP-based prediction methods. Strategies like SNP selection, SNP weighting, and use of causative SNPs from sequence analysis can be incorporated in APY without additional cost. The APY removes size limitations from ssGBLUP and facilitates a model with a complex genetic architecture. MenosABSTRACT.
The purpose of this study was to evaluate properties of the inverse of the genomic relationship matrix derived with the algorithm for proven and young (APY) and the accuracy of genomic selection in single-step genomic best linear unbiased prediction (ssGBLUP). The APY implements genomic recursions on a subset of genotyped animals. When that subset is small, the cost of APY is approximately linear in memory and computations, effectively removing restrictions on the number of genotypes. Tests involved 10 102 702 final scores from 6 930 618 Holstein cows. A total of 100 000 animals with genotypes were used in the analyses and included 23 174 sires, 27 215 cows and 49 611 young animals. Genomic estimated breeding values (GEBVs) were calculated using ssGBLUP with a regular inverse of the genomic relationship matrix (G) and with G inverse from APY. Many subsets were tested including only sires, only cows and random samples from 2 000 to 20 000 animals. When the number of animals in the subset was ≥15,000, the correlations between GEBV with APY and
GEBV with the regular inverse were ≥0.99. Best convergence rate was achieved with random samples. A theory on APY was derived and is based on the fact that additive effects of animals in the subset are linear functions of the effects of independent chromosome segments (ICSs); the number of segments is a function of the effective population size. Accuracy of GEBV with APY can be slightly superior to that of a regular... Presentar Todo |
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Palabras claves : |
BIG POPULATION; GENOMIC RECURSION; INVERSION; SINGLE-STEP METHOD. |
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Asunto categoría : |
-- |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/12204/1/1387-2387-1-PB.pdf
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Marc : |
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100 1 $aMISZTAL, I.
245 $aEfficient inversion of genomic relationship matrix by the Algorithm for Proven and Young (APY).$h[electronic resource]
260 $c2015
520 $aABSTRACT. The purpose of this study was to evaluate properties of the inverse of the genomic relationship matrix derived with the algorithm for proven and young (APY) and the accuracy of genomic selection in single-step genomic best linear unbiased prediction (ssGBLUP). The APY implements genomic recursions on a subset of genotyped animals. When that subset is small, the cost of APY is approximately linear in memory and computations, effectively removing restrictions on the number of genotypes. Tests involved 10 102 702 final scores from 6 930 618 Holstein cows. A total of 100 000 animals with genotypes were used in the analyses and included 23 174 sires, 27 215 cows and 49 611 young animals. Genomic estimated breeding values (GEBVs) were calculated using ssGBLUP with a regular inverse of the genomic relationship matrix (G) and with G inverse from APY. Many subsets were tested including only sires, only cows and random samples from 2 000 to 20 000 animals. When the number of animals in the subset was ≥15,000, the correlations between GEBV with APY and GEBV with the regular inverse were ≥0.99. Best convergence rate was achieved with random samples. A theory on APY was derived and is based on the fact that additive effects of animals in the subset are linear functions of the effects of independent chromosome segments (ICSs); the number of segments is a function of the effective population size. Accuracy of GEBV with APY can be slightly superior to that of a regular inverse. The inverse with APY is computed from G, which in turn is derived from single nucleotide polymorphism (SNP) BLUP and indirectly from BayesB or other SNP-based prediction methods. Strategies like SNP selection, SNP weighting, and use of causative SNPs from sequence analysis can be incorporated in APY without additional cost. The APY removes size limitations from ssGBLUP and facilitates a model with a complex genetic architecture.
653 $aBIG POPULATION
653 $aGENOMIC RECURSION
653 $aINVERSION
653 $aSINGLE-STEP METHOD
700 1 $aFRAGOMENI, B.
700 1 $aLOURENÇO, D. A. L.
700 1 $aTSURUTA, S.
700 1 $aMASUDA, Y.
700 1 $aAGUILAR, I.
700 1 $aLEGARRA, A.
700 1 $aLAWLOR, T. J.
773 $tInterbull Bulletin, 2015$gv. 49, p. 111-116.
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