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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