Training Set Determination for Genomic Selection

Determining training set for genomic selection using a genetic algorithm (Holland J.H. (1975) ) 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) ), PEV-score (Akdemir D. et al. (2015) ) and CD-score (Laloe D. (1993) ). 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.


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install.packages("TSDFGS")

1.0 by Jen-Hsiang Ou, 3 months ago


https://tsdfgs.oumark.me


Report a bug at https://gitlab.com/oumark/TSDFGS/issues


Browse source code at https://github.com/cran/TSDFGS


Authors: Jen-Hsiang Ou and Chen-Tuo Liao


Documentation:   PDF Manual  


GPL (>= 3) license


Imports Rcpp

Linking to Rcpp, RcppEigen


See at CRAN