Code for "Using machine learning to combine genetic and environmental data for maize grain yield predictions across multi-environment trials" (Fernandes et. al 2024)
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Updated
Jul 23, 2024 - Python
Code for "Using machine learning to combine genetic and environmental data for maize grain yield predictions across multi-environment trials" (Fernandes et. al 2024)
An R package for the Latent Environmental & Genetic InTeraction (LEGIT) model
See https://biometris.github.io/statgenGxE for a full description
Genome-wide association analysis of phenotypic plasticity in the maize nested association mapping population
SAS macros for the Latent Environmental & Genetic InTeraction (LEGIT) model
Your one-stop solution for comprehensive genotype × environment interaction and stability analysis (AMMI model) using the metan package. Save time, perform analyses for all traits at once, and gain insightful visualizations effortlessly!"
Joint meta-analysis of 2-df gene and gene-environment tests in GWAS.
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