An efficient genomic prediction method without the direct inverse of the genomic relationship matrix - Liu, Hailan; Xia, Chao; Lan, Hai (Frontiers in Plant Science, 2022)
The GBLUP, the most widely used genomic prediction (GP) method, consumes large amount of computational resources with the increase of the training population size due to the inverse of genomic relationship matrix (GRM). Therefore, we develop a new genomic prediction method (RHEPCG) avoiding the direct inverse of the GRM via combining randomized Haseman-Elston (HE) regression (RHE-reg) and preconditioned conjugate gradient (PCG) in this study. The simulation results demonstrate that RHEPCG not only achieves similar predictive accuracy with GBLUP in most cases, but also reduce computational time significantly. As for the real data, RHEPCG shows similar or better predictive accuracy in the 7 traits of the Arabidopsis thaliana F2 population and the 4 traits of the Sorghum bicolor RIL population compared with GBLUP. It is indicated that RHEPCG is a practical alternative to GBLUP with better computational efficiency.