Título
Replication Data for: Approximate kernels for large data sets In genome-based prediction
Autor
Osval Antonio Montesinos-Lopez
Johannes Martini
Paulino Pérez-Rodríguez
Jose Crossa
Nivel de Acceso
Acceso Abierto
Descripción
Abstracto - The rapid development of molecular markers and sequencing technologies has made it possible to use genomic selection (GS) and genomic prediction (GP) in animal and plant breeding. However, computational difficulties arise when the number of observations is large. This five datasets provided here were used to support a comparative analysis of two genomic-enabled prediction models: the full genomic method single environment (FGSE) and the approximate kernel method for a single environment model (APSE). The data were also used to compare the full genomic method with genotype × environment model (FGGE) to the approximate kernel method with genotype × environment interaction (APGE). The results of the analyses are described in the related publication.
Editor
International Maize and Wheat Improvement Center
Fecha de publicación
2020
Tipo de recurso
Dataset
Recurso de información
Repositorio Orígen
Repositorio Institucional de Datos y Software de Investigación del CIMMYT
Descargas
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