SFSI: Sparse Family and Selection Index

Here we provide tools for the estimation of coefficients in penalized regressions when the (co)variance matrix of predictors and the covariance vector between predictors and response, are provided. These methods are extended to the context of a Selection Index (commonly used for breeding value prediction). The approaches offer opportunities such as the integration of high-throughput traits in genetic evaluations ('Lopez-Cruz et al., 2020') <doi:10.1038/s41598-020-65011-2> and solutions for training set optimization in Genomic Prediction ('Lopez-Cruz & de los Campos, 2021') <doi:10.1093/genetics/iyab030>.

Package details

AuthorMarco Lopez-Cruz [aut, cre], Gustavo de los Campos [aut], Paulino Perez-Rodriguez [ctb]
MaintainerMarco Lopez-Cruz <maraloc@gmail.com>
LicenseGPL-3
Version1.0.0
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("SFSI")

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SFSI documentation built on Oct. 1, 2021, 1:08 a.m.