12 Results
for author "Yue-wen Wang"
- Table 1Description of experimental data sets
Figure 1(A–D) Accuracy of estimated marker effects in computer simulations using independent predictor variables. Simulations were conducted according to procedure 1 (Figure S6). In each scenario p = 2000 independent markers were simulated and h2 = 0.75 was used to simulate n phenotypic records. The normalized L2 errors of LASSO, the elastic net, BayesB, and RR-BLUP are displayed as heat maps for a grid of 20 values between 0.05 and 1.00 for the determinedness level n/p and model complexity level p0/n, respectively. The color key presents the normalized L2 error averaged over four replications for each scenario.
Figure 2Averaged normalized L2 error vs. the averaged sensitivity of LASSO across all 400 scenarios with four replications as in Figure 1. The sensitivity was evaluated as the empirical conditional probability that one of the min(p0, 20) largest true nonzero coefficients was identified.
Figure 3Normalized L2 error for LASSO, the elastic net, BayesB, and RR-BLUP as a function of the model complexity level. Curves were extracted from the surfaces in Figure 1 by fixing the determinedness level n/p at 0.05 and 0.50, respectively.
Figure 4Normalized L2 error for LASSO, the elastic net, BayesB, and RR-BLUP as a function of the model complexity level for different trait heritabilities (h2 = 0.50 and 1.00) and n/p = 0.5. The simulations were conducted according to procedure 1 (Figure S6).- Table 2Predictive abilities in computer simulations using LASSO, the elastic net, and RR-BLUP
Figure 5Meta-analysis of relative performance of BayesB compared to RR-BLUP with results from the literature. Results were extracted from the studies in Zhong et al. (2009), Daetwyler et al. (2010), Meuwissen and Goddard (2010), and Zhang et al. (2010), differing with respect to the number of QTL (NQTL) and sample size (n) of the training data set. Relative performance is defined as the ratio of accuracy or predictive ability of BayesB over RR-BLUP.- Table 3Predictive abilities obtained with LASSO, the elastic net, BayesB, and RR-BLUP for three experimental data sets
Figure 6(A–C) Heat maps for the normalized L2 error of LASSO with correlated predictor variables. The correlation structure of the simulated marker data was superimposed from the three experimental data sets (rice, wheat, and Arabidopsis). The simulations were conducted according to procedure 3 (Figure S6). Each of the 400 scenarios (p = 2000 and h2 = 0.75) was repeated 10 times and results were averaged over replications.