Package: TSDFGS
Type: Package
Title: Training Set Determination for Genomic Selection
Version: 1.0
Date: 2019-03-06
Author: Jen-Hsiang Ou and Chen-Tuo Liao
Maintainer: Jen-Hsiang Ou<oumark.me@outlook.com>
Description: Determining training set for genomic selection using a genetic algorithm (Holland J.H. (1975) <DOI:10.1145/1216504.1216510>) or simple exchange algorithm (change an individual every iteration). Three different criteria are used in both algorithms, which are r-score (Ou J.H., Liao C.T. (2018) <DOI:10.6342/NTU201802290>), PEV-score (Akdemir D. et al. (2015) <DOI:10.1186/s12711-015-0116-6>) and CD-score (Laloe D. (1993) <DOI:10.1186/1297-9686-25-6-557>). Phenotypic data for candidate set is not necessary for all these methods. By using it, one may readily determine a training set that can be expected to provide a better training set comparing to random sampling.
URL: https://tsdfgs.oumark.me
BugReports: https://gitlab.com/oumark/TSDFGS/issues
License: GPL (>= 3)
Imports: Rcpp (>= 1.0.0)
LinkingTo: Rcpp, RcppEigen
NeedsCompilation: yes
Packaged: 2019-03-06 10:09:26 UTC; mark
Repository: CRAN
Date/Publication: 2019-03-07 17:42:53 UTC
Built: R 3.6.1; x86_64-conda_cos6-linux-gnu; 2019-12-11 19:29:46 UTC; unix
