Here we provide tools for the estimation of regression coefficients in penalized problems providing the (co)variance matrix of predictors (X'X) and the covariance vector between predictors and response (X'y). The methods are extended in the context of a Selection Index (commonly used for breeding value prediction). These approaches offer opportunities such as integrating high-throughput phenotypes in genetic evaluations (Lopez-Cruz et al., 2020. doi:10.1038/s41598-020-65011-2) and solutions for training set optimization in Genomic Selection.
|Author||Marco Lopez-Cruz, Gustavo de los Campos|
|Maintainer||Marco Lopez-Cruz <firstname.lastname@example.org>|
|Package repository||View on GitHub|
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