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

0

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