From: A review of deep learning applications for genomic selection
A | Species | Trait | OLS | RR | LR | ER | BRR | MLP |
---|---|---|---|---|---|---|---|---|
Arabidopsis | Dry Matter | 0.36 | 0.4 | 0.4 | 0.42 | 0.39 | 0.4 | |
Flowering | 0.8 | 0.82 | 0.83 | 0.82 | 0.82 | 0.86 | ||
Maize | Flowering | 0.22 | 0.33 | 0.32 | 0.33 | 0.32 | 0.35 | |
GY | 0.47 | 0.59 | 0.49 | 0.51 | 0.57 | 0.55 | ||
Wheat | SGN | 0.15 | 0.27 | 0.33 | 0.36 | 0.28 | 0.33 | |
TYM | 0.59 | 0.61 | 0.74 | 0.73 | 0.64 | 0.76 | ||
B | Species | Trait | Method | 10kBEST | 10kUNIF | 50kBEST | 50kUNIF | |
Human | Height | BayesB | 0.47 | 0.38 | 0.48 | 0.42 | ||
Height | BRR | 0.47 | 0.37 | 0.47 | 0.39 | |||
Height | MLP | 0.45 | 0.36 | 0.45 | 0.39 | |||
Height | CNN | 0.44 | 0.34 | 0.42 | 0.29 | |||
HBMD | BayesB | 0.28 | 0.22 | 0.26 | 0.24 | |||
HBMD | BRR | 0.28 | 0.21 | 0.24 | 0.22 | |||
HBMD | MLP | 0.15 | 0.11 | 0.07 | 0.09 | |||
HBMD | CNN | 0.27 | 0.18 | 0.10 | 0.11 |