TSDFGS: Training Set Determination for Genomic Selection
Finds a training set for genomic selection and the size it needs.
The r-score of Ou and Liao (2019) <doi:10.1007/s00122-019-03387-0> is derived
from Pearson's correlation between the genomic estimated breeding values and the
phenotypic values of the test set. optTrain() searches for a good training set,
and SSDFGS() searches for its size. Eighteen criteria are available to score or
optimize a training set, among them A-, D-, E- and G-optimality, PEVmax, MSPE,
CDmean, CDmax, and genomic relationship criteria (Chen et al. (2024)
<doi:10.1007/s00122-024-04766-y>; Fernandez-Gonzalez et al. (2023)
<doi:10.1007/s00122-023-04265-6>). The computation uses 'Rcpp' and 'RcppEigen',
and independent searches can run on several threads with 'OpenMP'.
| Version: |
3.0.0 |
| Depends: |
R (≥ 4.0) |
| Imports: |
Rcpp, stats |
| LinkingTo: |
Rcpp, RcppEigen |
| Suggests: |
ggplot2, testthat (≥ 3.0.0) |
| Published: |
2026-11-12 |
| DOI: |
10.32614/CRAN.package.TSDFGS |
| Author: |
Jen-Hsiang Ou 
[aut, cre] (affiliation: Department of Medical Genetics, National
Taiwan University Hospital),
Po-Ya Wu [aut],
Chen-Tuo Liao
[aut, ths] |
| Maintainer: |
Jen-Hsiang Ou <oumark.me at outlook.com> |
| BugReports: |
https://github.com/oumarkme/TSDFGS/issues |
| License: |
GPL (≥ 3) |
| URL: |
https://www.oumark.net/TSDFGS/, https://github.com/oumarkme/TSDFGS |
| NeedsCompilation: |
yes |
| SystemRequirements: |
C++17 |
| Materials: |
README, NEWS |
| In views: |
Agriculture |
| CRAN checks: |
TSDFGS results |
Documentation:
Downloads:
Linking:
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