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| Registros recuperados : 33 | |
| 1. |  | BERMANN, M.; MISZTAL, I.; LOURENCO, D.; AGUILAR, I.; LEGARRA, A. Definition of reliabilities for models with metafounders. [289] Part 17 - Challenges - improving genomic prediction. 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_289 1217-1220. Article history: Published online: February 9, 2023. -- Corresponding author: A. Legarra, email: andres.legarra@inrae.fr -- Acknowledgment: This work received financing from European Unions' Horizon 2020 Research & Innovation Programme,...| Biblioteca(s): INIA Las Brujas. |
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| 2. | | BERMANN, M.; AGUILAR, I.; LOURENCO , D.; MISZTAL, I.; LEGARRA, A. Reliabilities of estimated breeding values in models with metafounders. Research article. Genetics, Selection, Evolution : GSE, 2023, volume55, issue 1, article 6. OPEN ACCESS. doi: https://doi.org/10.1186/s12711-023-00778-2 Article history: Received 29 June 2022; Accepted 04 January 2023; Published 23 January 2023. -- Corresponding author: Matias Bermann, Department of Animal and Dairy Science, University of Georgia, Athens, GA, USA, email: mbermann@uga.edu...| Biblioteca(s): INIA Las Brujas. |
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| 3. | | ZHANG, X.; LOURENCO, D.; MISZTAL, I.; AGUILAR, I.; LEGARRA, A. Weighted single-step genomic BLUP: an iterative approach for accurate calculation of GEBV and GWAS. Volume Methods and Tools: Statistical and genomic tools for mapping QTL and genes (Posters), 681. In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 10., Vancouver, BC, Canada, August 17-22, 2014. p.681.| Biblioteca(s): INIA Las Brujas. |
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| 4. | | ZHANG, X.; LOURENCO, D.; AGUILAR, I.; LEGARRA, A.; MISZTAL, I. Weighting strategies for single-step genomic BLUP: An iterative approach for accurate calculation of GEBV and GWAS. Frontiers in Genetics, 19 August 2016, Volume 7, Issue AUG, Article number 151. OPEN ACCESS Article history: Received 15 May 2016 // Accepted 04 August 2016 // Published 19 August 2016.
Specialty section:
This article was submitted to Statistical Genetics and Methodology, a section of the journal Frontiers in Genetics.| Biblioteca(s): INIA Las Brujas. |
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| 5. | | 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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| 6. | | 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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| 7. | | 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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| 8. | | 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/s12711-022-00752-4| Biblioteca(s): INIA Las Brujas. |
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| 9. | | MISZTAL, I.; AGUILAR, I.; LOURENCO, D.; MA, L.; STEIBEL, J.P. Emerging issues in genomic selection. Animal Genetics and Genomics. Journal of Animal Science, June 2021, Volume 99, Issue 61, skab092. OPEN ACCESS. Doi: https://doi.org/10.1093/jas/skab092 Article history: Received 23 January 2021; Accepted 26 March 2021; Advance Access publication March 27, 2021.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License...| Biblioteca(s): INIA Las Brujas. |
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| 10. | | FRAGOMENI, B.O.; MISZTAL, I.; LOURENCO, D.L.; AGUILAR, I.; OKIMOTO, R.; MUIR, W.M. Changes in variance explained by top SNP windows over generations for three traits in broiler chicken Frontiers in Genetics, 2014, v.5, no.Oct., Article number 332. OPEN ACCESS. Article history: Published 01 October 2014.| Biblioteca(s): INIA Las Brujas. |
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| 11. | | 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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| 12. | | 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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| 13. | | 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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| 14. | | LOURENCO, D.A.L.; MISZTAL, I.; WANG, H.; AGUILAR, I.; TSURUTA, S.; BERTRAND, J.K. Prediction accuracy for a simulated maternally affected trait of beef cattle using different genomic evaluation models. Journal of Animal Science, 2013, v.91, no.9, p.4090-4098. Article history: Published online July 26, 2013.
This study was partially funded by the American Angus Association (St. Joseph, MO) and the USDA Agriculture and Food Research Initiative (Grant no. 2009-65205-05665 from the USDA National...| Biblioteca(s): INIA Las Brujas. |
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| 15. | | 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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| 16. | | 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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| 17. | | GARCÍA, A.; AGUILAR, I.; LEGARRA, A.; TSURUTA, S.; MISZTAL, I.; LOURENCO, D. Theoretical accuracy for indirect predictions based on SNP effects from single-step GBLUP. Genetics, Selection, Evolution : GSE, 2022, Volume 54, Issue 1, Pages 66. OPEN ACCESS. doi: https://doi.org/10.1186/s12711-022-00752-4 Article history: Received 22 March 2022; Accepted 23 August 2022; Published 27 September 2022.| Biblioteca(s): INIA Las Brujas. |
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| 18. | | 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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| 19. | | LOURENCO, D.A.L.; MISZTAL, I.; TSURUTA, S.; AGUILAR, I.; LAWLOR, T.J.; FORNI, S.; WELLER, J.I. Are evaluations on young genotyped animals benefiting from the past generations?. Journal of Dairy Science, 2014, v.97, no.6, p.3930-3942. OPEN ACCESS Article history: Received November 26, 2013. // Accepted February 11, 2014. OPEN ACCESS| Biblioteca(s): INIA Las Brujas. |
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| 20. | | LOURENCO, D.A.L.; FRAGOMENI, B.O.; TSURUTA, S.; AGUILAR, I.; ZUMBACH, B.; HAWKEN, R.J.; LEGARRA, A.; MISZTAL, I. Accuracy of estimated breeding values with genomic information on males, females, or both: An example on broiler chicken. Genetics Selection Evolution, 2015, v. 242, p. 47-56. OPEN ACCESS. Article history: Received: 14 October 2014 / Accepted: 22 June 2015 / Published: 02 July 2015.| Biblioteca(s): INIA Las Brujas. |
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| Registros recuperados : 33 | |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
04/07/2019 |
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Actualizado : |
04/07/2019 |
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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 : |
AGUILAR, I.; LEGARRA, A.; CARDOSO, F.; MASUDA, Y.; LOURENCO, D.; MISZTAL, I. |
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Afiliación : |
IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ANDRÉS LEGARRA, INRA (Institut National de la Recherche Agronomique); FERNANDO CARDOSO, Department of Animal Science, Federal University of Pelotas, Brazil; Embrapa Pecuária Sul, Brazil; YUTAKA MASUDA, Department of Animal and Dairy Science, University of Georgia, United States; DANIELA LOURENCO, Department of Animal and Dairy Science, University of Georgia, United States; IGNACY MISZTAL, Department of Animal and Dairy Science, University of Georgia, United States. |
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Título : |
Frequentist p-values for large-scale-single step genome-wide association, with an application to birth weight in American Angus cattle. (Short Communication) |
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Fecha de publicación : |
2019 |
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Fuente / Imprenta : |
Genetics Selection Evolution, 20 June 2019, v. 51, Issue 1, Article number 28. OPEN ACCESS. |
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ISSN : |
0999-193X |
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DOI : |
10.1186/s12711-019-0469-3 |
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Idioma : |
Inglés |
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Notas : |
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 Initiative Competitive Grants No. 2015-67015-22936 from the US Department of Agriculture?s National Institute of Food and Agriculture.
Availability of data and materials: The data that support the fndings of this study were provided from the American Angus Association but restrictions apply to the availability of these data, which were used under license for the current study, and thus are not publicly available. The methods described here are included using ?OPTION snp_p_value? in the parameter fle in software blupf90 (factorization of the mixed model equations and solving of the SSGBLUP equations) and postGSf90
(backsolving of snp efects and computation of p-values), available at http://nce.ads.uga.edu/software/. |
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Contenido : |
ABSTRACT.
Background: Single-step genomic best linear unbiased prediction (SSGBLUP) is a comprehensive method for genomic prediction. Point estimates of marker effects from SSGBLUP are often used for genome-wide association studies (GWAS) without a formal framework of hypothesis testing. Our objective was to implement p-values for single-marker GWAS studies within the single-step GWAS (SSGWAS) framework by deriving computational algorithms and procedures, and by applying these to a large beef cattle population. Methods: P-values were obtained based on the prediction error (co)variances for single nucleotide polymorphisms (SNPs), which were obtained from the prediction error (co)variances of genomic predictions based on the inverse of the coefficient matrix and formulas to estimate SNP effects. Results: Computation of p-values took a negligible time for a dataset with almost 2 million animals in the pedigree and 1424 genotyped sires, and no inflation of statistics was observed. The SNPs that passed the Bonferroni threshold of 10-5.9 were the same as those that explained the highest proportion of additive genetic variance, but even at the same significance levels and effects, some of them explained less genetic variance due to lower allele frequency. Conclusions: The use of a p-value for SSGWAS is a very general and efficient strategy to identify quantitative trait loci (QTL). It can be used for complex datasets such as those used in animal breeding, where only a proportion of the pedigreed animals are genotyped.
© 2019 The Author(s). MenosABSTRACT.
Background: Single-step genomic best linear unbiased prediction (SSGBLUP) is a comprehensive method for genomic prediction. Point estimates of marker effects from SSGBLUP are often used for genome-wide association studies (GWAS) without a formal framework of hypothesis testing. Our objective was to implement p-values for single-marker GWAS studies within the single-step GWAS (SSGWAS) framework by deriving computational algorithms and procedures, and by applying these to a large beef cattle population. Methods: P-values were obtained based on the prediction error (co)variances for single nucleotide polymorphisms (SNPs), which were obtained from the prediction error (co)variances of genomic predictions based on the inverse of the coefficient matrix and formulas to estimate SNP effects. Results: Computation of p-values took a negligible time for a dataset with almost 2 million animals in the pedigree and 1424 genotyped sires, and no inflation of statistics was observed. The SNPs that passed the Bonferroni threshold of 10-5.9 were the same as those that explained the highest proportion of additive genetic variance, but even at the same significance levels and effects, some of them explained less genetic variance due to lower allele frequency. Conclusions: The use of a p-value for SSGWAS is a very general and efficient strategy to identify quantitative trait loci (QTL). It can be used for complex datasets such as those used in animal breeding, where only a proportion of... Presentar Todo |
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Palabras claves : |
ANIMALIA. |
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Asunto categoría : |
-- |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/12994/1/s12711-019-0469-3.pdf
https://gsejournal.biomedcentral.com/track/pdf/10.1186/s12711-019-0469-3
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Marc : |
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100 1 $aAGUILAR, I.
245 $aFrequentist p-values for large-scale-single step genome-wide association, with an application to birth weight in American Angus cattle. (Short Communication)$h[electronic resource]
260 $c2019
500 $aArticle 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 Initiative Competitive Grants No. 2015-67015-22936 from the US Department of Agriculture?s National Institute of Food and Agriculture. Availability of data and materials: The data that support the fndings of this study were provided from the American Angus Association but restrictions apply to the availability of these data, which were used under license for the current study, and thus are not publicly available. The methods described here are included using ?OPTION snp_p_value? in the parameter fle in software blupf90 (factorization of the mixed model equations and solving of the SSGBLUP equations) and postGSf90 (backsolving of snp efects and computation of p-values), available at http://nce.ads.uga.edu/software/.
520 $aABSTRACT. Background: Single-step genomic best linear unbiased prediction (SSGBLUP) is a comprehensive method for genomic prediction. Point estimates of marker effects from SSGBLUP are often used for genome-wide association studies (GWAS) without a formal framework of hypothesis testing. Our objective was to implement p-values for single-marker GWAS studies within the single-step GWAS (SSGWAS) framework by deriving computational algorithms and procedures, and by applying these to a large beef cattle population. Methods: P-values were obtained based on the prediction error (co)variances for single nucleotide polymorphisms (SNPs), which were obtained from the prediction error (co)variances of genomic predictions based on the inverse of the coefficient matrix and formulas to estimate SNP effects. Results: Computation of p-values took a negligible time for a dataset with almost 2 million animals in the pedigree and 1424 genotyped sires, and no inflation of statistics was observed. The SNPs that passed the Bonferroni threshold of 10-5.9 were the same as those that explained the highest proportion of additive genetic variance, but even at the same significance levels and effects, some of them explained less genetic variance due to lower allele frequency. Conclusions: The use of a p-value for SSGWAS is a very general and efficient strategy to identify quantitative trait loci (QTL). It can be used for complex datasets such as those used in animal breeding, where only a proportion of the pedigreed animals are genotyped. © 2019 The Author(s).
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773 $tGenetics Selection Evolution, 20 June 2019$gv. 51, Issue 1, Article number 28. OPEN ACCESS.
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