Training set optimization under population structure in genomic selection.

ABSTRACT:

Key message

Population structure must be evaluated before optimization of the training set population. Maximizing the phenotypic variance captured by the training set is important for optimal performance. The optimization of the training set (TRS) in genomic selection has received much interest in both animal and plant breeding, because it is critical to the accuracy of the prediction models. In this study, five different TRS sampling algorithms, stratified sampling, mean of the coefficient of determination (CDmean), mean of predictor error variance (PEVmean), stratified CDmean (StratCDmean) and random sampling, were evaluated for prediction accuracy in the presence of different levels of population structure. In the presence of population structure, the most phenotypic variation c

SUBMITTER: Isidro J 

PROVIDER: S-EPMC4282691 | biostudies-literature | 2015 Jan

REPOSITORIES: biostudies-literature