Ensemble AnalySis with Interpretable Genomic Prediction (EasiGP): Computational tool for interpreting ensembles of genomic prediction models.

ABSTRACT: An ensemble of multiple genomic prediction models has grown in popularity due to consistent prediction performance improvements in crop breeding. However, technical tools that analyze the predictive behavior at the genome level are lacking. Here, we develop a computational tool called Ensemble AnalySis with Interpretable Genomic Prediction (EasiGP) that uses circos plots to visualize how different genomic prediction models quantify contributions of marker effects to trait phenotypes. As a demonstration of EasiGP, multiple genomic prediction models, spanning conventional statistical and machine learning algorithms, were used to infer the genetic architecture of days to anthesis (DTA) in a maize mapping population. The results indicate that genomic prediction models can capture different vie

SUBMITTER: Tomura S 

PROVIDER: S-EPMC12528827 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature