TSDFGS: Training Set Determination for Genomic Selection
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.
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