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

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.

Data and Resources

Additional Info

Field Value
Author Cuevas, Jaime, Montesinos-López, Osval A., Martini, Johannes, Pérez-Rodríguez, Paulino, Lillemo, Morten, Crossa, Jose
Maintainer CIMMYT Research Data & Software Repository Network
Last Updated January 20, 2025, 15:47 (UTC)
Created January 20, 2025, 15:47 (UTC)
contributor Dreher, Kate
creator Cuevas, Jaime
date 2020-05-24T00:00:00
harvest_object_id 1ee71488-7a85-4ad8-9add-60d400d0e936
harvest_source_id a58b0729-e941-4389-816d-5823f01c0d28
harvest_source_title CIMMYT Research Data
identifier https://hdl.handle.net/11529/10548425
language English
metadata_modified 2024-10-26T07:00:04
set_spec cimmytdatadvn