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Table 2 Scenario 1: Results for the trait controlled by small gene effects with heritability 0.30

From: Ridge, Lasso and Bayesian additive-dominance genomic models

Method h2a h2d cor_a byg_a cor_d byg_d Vd/Va Number of criteria scored as best
Parametric 0.21 ± 0.01 0.10 ± 0.01 0.68 - 0.48 - 0.48 -
BRR (−2,-2) 0.15b ± 0.05 0.12b ± 0.05 0.63b ± 0.03 1.40 ± 0.33 0.31b ± 0.07 0.57b ± 0.23 0.77 5b
IBLASSO (4,-2) 0.12 ± 0.06 0.14 ± 0.05 0.62b ± 0.03 2.41 ± 1.82 0.28 ± 0.06 0.46 ± 0.24 1.19 1
IBLASSO (4,2) 0.14 ± 0.06 0.10b ± 0.06 0.63b ± 0.03 1.86 ± 1.14 0.29b ± 0.06 0.63b ± 0.42 0.81 4
BAYESA*B* (−2,6) 0.15b ± 0.06 0.10b ± 0.05 0.63b ± 0.03 1.51 ± 0.57 0.29b ± 0.06 0.69b ± 0.42 0.67 5b
BAYESA*B* (4,6) 0.15b ± 0.06 0.10b ± 0.05 0.63b ± 0.03 1.49b ± 0.56 0.29b ± 0.06 0.71b ± 0.43 0.65 6b
BAYESA*B* (−2,8) 0.15b ± 0.05 0.09b ± 0.05 0.63b ± 0.03 1.44b ± 0.47 0.29b ± 0.06 0.72b ± 0.42 0.61b 7b
RR-HET (-2–2) 0.11 ± 0.06 0.14 ± 0.05 0.62b ± 0.03 2.43 ± 1.74 0.28 ± 0.05 0.44 ± 0.23 1.24 1
BLASSO (4,2) 0.17b ± 0.09 0.13 ± 0.02 0.63b ± 0.03 1.44 ± 0.65 0.29b ± 0.05 3.20 ± 5.34 0.74 3
G-BLUP 0.15b ± 0.05 0.13 ± 0.06 0.63b ± 0.03 1.25b ± 0.35 0.31b ± 0.04 0.70b ± 0.30 0.83 5b
Pedigree 0.16b ± 0.03 0.07 ± 0.01 0.53 ± 0.03 0.96b ± 0.19 0.05 ± 0.02 0.20 ± 0.11 - 2
  1. bbest = highest + − 0.02 for h2a, h2d, cor a, cor d and Vd/Va; 0.5 to 1.5 for bya and byd; highest minus 2 for best criteria in the last column