A guidance of model selection for genomic prediction based on linear mixed models for complex traits.

The exploration of the relationship between genetic architecture (approximated by the Manhattan plot) and accuracy of the commonly used prediction models suggests that the models (i.e., DPR and AMB) that can model both sparse effects as well as infinitesimal effects perform better for diseases with highly significant SNPs.

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