Package: SFSI
Title: Sparse Family and Selection Index
Version: 1.4.1
Authors@R: c(
    person("Marco", "Lopez-Cruz", role = c("aut","cre"), email = "maraloc@gmail.com"),
    person("Gustavo", "de los Campos", role = c("aut"), email = "gustavoc@msu.edu"),
    person("Paulino", "Perez-Rodriguez", role = c("ctb"), email = "perpdgo@gmail.com"))
Date: 2024-08-23
Description: 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>.
URL: https://github.com/MarcooLopez/SFSI
LazyLoad: true
Depends: R (>= 3.6.0)
Imports: stats, scales, tensorEVD (>= 0.1.3), parallel, reshape2,
        viridis, igraph, stringr, ggplot2
Suggests: BGLR, knitr, rmarkdown
VignetteBuilder: knitr
Encoding: UTF-8
License: GPL-3
NeedsCompilation: yes
Packaged: 2024-08-23 21:12:17 UTC; marcolopez
Author: Marco Lopez-Cruz [aut, cre],
  Gustavo de los Campos [aut],
  Paulino Perez-Rodriguez [ctb]
Maintainer: Marco Lopez-Cruz <maraloc@gmail.com>
Repository: CRAN
Date/Publication: 2024-08-23 22:00:06 UTC
