A comparison of methods for training set optimization in genomic selection to discover the most favorable genotypes from a candidate population

The dataset was used in the article "<b>A comparison of methods for training set optimization in genomic selection to discover the most favorable genotypes from a candidate population</b>".In the dataset, inside each file, the file name containing kinship is the kinship matrix, the file name containing PC is the principal components matrix, the file name containing subpop is a vector represents the subpopulation of each individuals, and the file name containing pheno is the phenotype data.The tropical rice dataset is originally from Spindel<i> </i>et al. (2015) [1], The wheat dataset is originally from Kristensen et al. (2019) [2], The sorghum dataset is originally from Fernandez-Gonzalez et al. (2022) [3], and soybean dataset is originally from Stewart-Brown<i> </i>et al. (2019) [4].<br>Spindel J, Begum H, Akdemir D, Virk P, Collard B, et al. (2015) Genomic selection and association mapping in rice (<i>Oryza sativa</i>): effect of trait genetic architecture, training population composition, marker number and statistical model on accuracy of rice genomic selection in elite, tropical rice breeding lines. PLoS Genet 11: e1004982.Kristensen PS, Jensen J, Andersen JR, Guzmán C, Orabi J, Jahoor A (2019) Genomic prediction and genome-wide association studies of flour yield and alveograph quality traits using advanced winter wheat breeding material. Genes 210(9): 669.Fernandez-Gonzalez et al. (2022) A comparison of methods for training population optimization in genomic selection. Theor and Appl Genet 136:30Stewart-Brown, B. B., Song, Q., Vaughn, J. N., and Li, Z. (2019). Genomic selection for yield and seed composition traits within an applied soybean breeding program. Genes|Genomes|Genetics 9, 2253–2265.