Title

Replication Data for: Approximate kernels for large data sets In genome-based prediction

Author

Osval Antonio Montesinos-Lopez

Johannes Martini

Paulino Pérez-Rodríguez

Jose Crossa

Access level

Open Access

Description

Abstract - 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.

Publisher

International Maize and Wheat Improvement Center

Publish date

2020

Resource Type

Dataset

Source repository

Repositorio Institucional de Datos y Software de Investigación del CIMMYT

Downloads

0

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