TSDFGS: Training Set Determination for Genomic Selection

We propose an optimality criterion to determine the required training set, r-score, which is derived directly from Pearson's correlation between the genomic estimated breeding values and phenotypic values of the test set <doi:10.1007/s00122-019-03387-0>. This package provides two main functions to determine a good training set and its size.

Version: 2.0
Depends: R (≥ 2.10)
Imports: dplyr, ggplot2, latex2exp, lifecycle, parallel, Rcpp (≥
LinkingTo: Rcpp, RcppEigen
Published: 2022-06-07
Author: Jen-Hsiang Ou ORCID iD [aut, cre], Po-Ya Wu ORCID iD [aut], Chen-Tuo Liao ORCID iD [aut, ths]
Maintainer: Jen-Hsiang Ou <jen-hsiang.ou at imbim.uu.se>
BugReports: https://github.com/oumarkme/TSDFGS/issues
License: GPL (≥ 3)
URL: https://github.com/oumarkme/TSDFGS
NeedsCompilation: yes
Materials: README
CRAN checks: TSDFGS results


Reference manual: TSDFGS.pdf


Package source: TSDFGS_2.0.tar.gz
Windows binaries: r-devel: TSDFGS_2.0.zip, r-release: TSDFGS_2.0.zip, r-oldrel: TSDFGS_2.0.zip
macOS binaries: r-release (arm64): TSDFGS_2.0.tgz, r-oldrel (arm64): TSDFGS_2.0.tgz, r-release (x86_64): TSDFGS_2.0.tgz, r-oldrel (x86_64): TSDFGS_2.0.tgz
Old sources: TSDFGS archive


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