Published July 9, 2024 | Version 0.1.0
Dataset Open

Using machine learning to integrate genetic and environmental data to model genotype-by-environment interactions

  • 1. ROR icon University of Arkansas at Fayetteville
  • 2. ROR icon Universidade Federal de Viçosa

Description

Files generated from the study described in Fernandes et. al (2024) .

The file "cvs_h2s.csv" comprises the coefficient of variation and the Cullis heritability for each environment.

The file "all_predictions.csv" contains the predictions from all the models evaluated, in different cross-validation (CV) scenarios.

The file "coincidence_index.csv" has the Coincidence Index (CI) for each CV and models evaluated in our study.

Our study used the multi-environment maize yield trials data from the Genomes to Fields 2022 initiative (Lima et. al 2024).

Files

all_predictions.csv

Files (288.2 MB)

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md5:a767b2a350ae3f97dc486b9796eab9ba
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md5:1bd664d216cc0112d0b26ae8b87d183d
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Additional details

Dates

Submitted
2024-09-07

Software

Repository URL
https://github.com/igorkf/Maize_GxE_Prediction
Programming language
Python, R, Shell