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Table 5 Scenario 4: Results for the trait controlled by mixed (major and small gene effects) inheritance model with heritability 0.50

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 best

Parametric

0.33 ± 0.01

0.21 ± 0.01

0.69

-

0.55

-

0.64

-

BRR (−2,-2)

0.25b ± 0.06

0.17 ± 0.04

0.69b ± 0.02

1.36b ± 0.24

0.42 ± 0.03

0.83b ± 0.18

0.67b

5

IBLASSO (4,-2)

0.24b ± 0.07

0.18 ± 0.04

0.69b ± 0.02

1.44b ± 0.30

0.41 ± 0.04

0.79b ± 0.20

0.74

4

IBLASSO (4,2)

0.25b ± 0.07

0.15 ± 0.04

0.69b ± 0.03

1.35b ± 0.27

0.42 ± 0.04

0.90b ± 0.26

0.61b

5

BAYESA*B* (−2,6)

0.26b ± 0.07

0.14 ± 0.03

0.69b ± 0.03

1.31b ± 0.26

0.42 ± 0.04

0.97b ± 0.03

0.55

4

BAYESA*B* (4,6)

0.26b ± 0.07

0.14 ± 0.04

0.69b ± 0.03

1.31b ± 0.26

0.42 ± 0.04

0.96b ± 0.28

0.55

4

BAYESA*B* (−2,8)

0.26b ± 0.07

0.14 ± 0.04

0.69b ± 0.03

1.29b ± 0.25

0.42 ± 0.04

0.99b ± 0.30

0.53

4

RR-HET (-2,–2)

0.23 ± 0.07

0.17 ± 0.04

0.69b ± 0.02

1.44b ± 0.30

0.41 ± 0.04

0.80b ± 0.20

0.74

3

BLASSO (4,2)

0.23 ± 0.08

0.21 ± 0.06

0.68b ± 0.03

1.37b ± 0.35

0.41 ± 0.03

0.86b ± 0.26

0.88

4

G-BLUP

0.25b ± 0.06

0.19 ± 0.04

0.70b ± 0.02

1.25b ± 0.03

0.46b ± 0.02

0.94b ± 0.20

0.76

6

Pedigree

0.20 ± 0.02

0.13 ± 0.01

0.45 ± 0.03

0.84b ± 0.11

0.08 ± 0.03

0.24 ± 0.10

-

1

  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