Differentially penalized regression to predict agronomic traits from metabolites and markers in wheat

Genomic prediction of agronomic traits as targets for selection in plant breeding programmes is increasingly common. The methods employed can also be applied to predict traits from other sources of covariates, such as metabolomics. However, prediction combining sets of covariates can be less accurate than using the best of the individual sets. We describe a method, termed Differentially Penalized Regression (DiPR), which uses standard ridge...