The effect of the H−1 scaling factors t and w on the structure of H in the single‑step procedure
Background: The single-step covariance matrix H combines the pedigree-based relationship matrix A with the more accurate information on realized relatedness of genotyped individuals represented by the genomic relationship matrix G. In particular, to improve convergence behavior of iterative approach...
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| Otros Autores: | , , , , , , , , , , |
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| Formato: | Libro |
| Lenguaje: | Inglés |
| Materias: | |
| Acceso en línea: | http://ri.agro.uba.ar/files/download/articulo/2018martini.pdf LINK AL EDITOR |
| Aporte de: | Registro referencial: Solicitar el recurso aquí |
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| 003 | AR-BaUFA | ||
| 005 | 20230914140539.0 | ||
| 008 | 180809t2018 xxu|||||o|||| 00| 0 eng d | ||
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| 024 | |a 10.1186/s12711-018-0386-x | ||
| 040 | |a AR-BaUFA | ||
| 245 | 1 | 0 | |a The effect of the H−1 scaling factors t and w on the structure of H in the single‑step procedure |
| 520 | |a Background: The single-step covariance matrix H combines the pedigree-based relationship matrix A with the more accurate information on realized relatedness of genotyped individuals represented by the genomic relationship matrix G. In particular, to improve convergence behavior of iterative approaches and to reduce inflation, two weights t and w have been introduced in the definition of H−1, which blend the inverse of a part of A with the inverse of G . Since the definition of this blending is based on the equation describing H−1, its impact on the structure of H is not obvious. In a joint discussion, we considered the question of the shape of H for non-trivial t and w. Results: Here, we present the general matrix H as a function of these parameters and discuss its structure and properties. Moreover, we screen for optimal values of t and w with respect to predictive ability, inflation and iterations up to convergence on a well investigated, publicly available wheat data set. Conclusion: Our results may help the reader to develop a better understanding for the effects of changes of t and w on the covariance model. In particular, we give theoretical arguments that as a general tendency, inflation will be reduced by increasing t or by decreasing w. | ||
| 653 | |a CONVERGENCE | ||
| 653 | |a CONVERGENT EVOLUTION | ||
| 653 | |a COVARIANCE ANALYSIS | ||
| 653 | |a DATA SET | ||
| 653 | |a GENOMICS | ||
| 653 | |a GENOTYPE | ||
| 653 | |a PARAMETERIZATION | ||
| 653 | |a PREDICTION | ||
| 653 | |a REDUCTION | ||
| 653 | |a RELATEDNESS | ||
| 653 | |a WHEAT | ||
| 653 | |a TRITICUM AESTIVUM | ||
| 700 | 1 | |9 67704 |a Martini, Johannes W. R. |u KWS SAAT SE, Einbeck, Germany. | |
| 700 | 1 | |9 37966 |a Schrauf, Matías Florián |u Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Animal. Buenos Aires, Argentina. | |
| 700 | 1 | |9 33814 |a García Baccino, Carolina Andrea |u Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Animal. Buenos Aires, Argentina. | |
| 700 | 1 | |a Pimentel, Eduardo C. G. |u Institute of Animal Breeding, Bavarian State Research Center for Agriculture. Poing‑Grub, Germany. |9 67707 | |
| 700 | 1 | |9 13019 |a Munilla Leguizamón, Sebastián |u Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Animal. Buenos Aires, Argentina. |u CONICET. Buenos Aires, Argentina. | |
| 700 | 1 | |9 37756 |a Rogberg Muñoz, Andrés |u Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Animal. Buenos Aires, Argentina. |u CONICET. Universidad Nacional de La Plata. Buenos Aires, Argentina. |u Universidad Nacional de La Plata. Facultad de Ciencias Veterinarias. Instituto de Genética Veterinaria Ing. Fernando Noel Dulout. La Plata, Argentina. | |
| 700 | 1 | |9 12817 |a Cantet, Rodolfo Juan Carlos |u Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Animal. Buenos Aires, Argentina. |u Universidad de Buenos Aires. Facultad de Agronomía.. Instituto de Investigaciones en Producción Animal (INPA). Buenos Aires, Argentina. |u CONICET. Universidad de Buenos Aires.Instituto de Investigaciones en Producción Animal (INPA). Buenos Aires, Argentina. | |
| 700 | 1 | |a Reimer, Christian |u University of Goettingen. Animal Breeding and Genetics Group, Center for Integrated Breeding Research. Goettingen, Germany. |9 67799 | |
| 700 | 1 | |a Gao, Ning |u University of Goettingen. Animal Breeding and Genetics Group, Center for Integrated Breeding Research. Goettingen, Germany. |u South China Agricultural University. College of Animal Science. Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro‑animal Genomics and Molecular Breeding. Guangzhou, China. |9 67800 | |
| 700 | 1 | |a Wimmer, Valentin |u KWS SAAT SE, Einbeck, Germany. |9 67801 | |
| 700 | 1 | |9 67802 |a Simianer, Henner |u University of Goettingen. Animal Breeding and Genetics Group, Center for Integrated Breeding Research. Goettingen, Germany. | |
| 773 | 0 | |t Genetics selection evolution |w (AR-BaUFA)SECS000092 |g Vol.50, no.16 (2018), 9 p., grafs. | |
| 856 | |f 2018martini |i En Internet |q application/pdf |u http://ri.agro.uba.ar/files/download/articulo/2018martini.pdf |x ARTI201808 | ||
| 856 | |u https://www.biomedcentral.com/ |z LINK AL EDITOR | ||
| 942 | |c ARTICULO | ||
| 942 | |c ENLINEA | ||
| 976 | |a AAG | ||