From: Multi-population genomic prediction using a multi-task Bayesian learning model
Ayrshire | Holstein | |||||
---|---|---|---|---|---|---|
SNP panel | Single-task | Pooling | Multi-task | Single-task | Pooling | Multi-task |
r(TBV, GEBV) | ||||||
ρ = 0.2 | ||||||
800 k | 0.71 ± 0.02 | 0.56 ± 0.04 | 0.75 ± 0.02 | 0.91 ± 0.01 | 0.90 ± 0.01 | 0.91 ± 0.01 |
400 k | 0.64 ± 0.04 | 0.53 ± 0.04 | 0.73 ± 0.03 | 0.90 ± 0.01 | 0.86 ± 0.01 | 0.90 ± 0.01 |
200 k | 0.60 ± 0.05 | 0.50 ± 0.04 | 0.68 ± 0.02 | 0.88 ± 0.01 | 0.84 ± 0.01 | 0.88 ± 0.01 |
100 k | 0.57 ± 0.04 | 0.47 ± 0.04 | 0.63 ± 0.03 | 0.84 ± 0.01 | 0.81 ± 0.02 | 0.84 ± 0.01 |
ρ = 0.8 | ||||||
800 k | 0.67 ± 0.05 | 0.76 ± 0.02 | 0.83 ± 0.01 | 0.92 ± 0.01 | 0.92 ± 0.01 | 0.93 ± 0.01 |
400 k | 0.66 ± 0.05 | 0.72 ± 0.02 | 0.80 ± 0.01 | 0.90 ± 0.01 | 0.89 ± 0.01 | 0.90 ± 0.01 |
200 k | 0.66 ± 0.04 | 0.68 ± 0.02 | 0.76 ± 0.01 | 0.86 ± 0.01 | 0.86 ± 0.01 | 0.86 ± 0.01 |
100 k | 0.61 ± 0.04 | 0.63 ± 0.04 | 0.72 ± 0.02 | 0.83 ± 0.01 | 0.83 ± 0.01 | 0.84 ± 0.01 |
b(TBV, GEBV) | ||||||
ρ = 0.2 | ||||||
800 k | 1.06 ± 0.05 | 0.73 ± 0.05 | 1.04 ± 0.05 | 0.98 ± 0.02 | 1.01 ± 0.01 | 0.98 ± 0.01 |
400 k | 1.06 ± 0.05 | 0.76 ± 0.06 | 1.06 ± 0.05 | 0.99 ± 0.02 | 1.00 ± 0.01 | 0.98 ± 0.01 |
200 k | 1.02 ± 0.06 | 0.75 ± 0.05 | 1.03 ± 0.04 | 1.00 ± 0.01 | 0.99 ± 0.01 | 0.98 ± 0.01 |
100 k | 1.00 ± 0.06 | 0.75 ± 0.05 | 1.03 ± 0.06 | 1.00 ± 0.01 | 1.00 ± 0.02 | 0.99 ± 0.01 |
ρ = 0.8 | ||||||
800 k | 1.10 ± 0.06 | 0.90 ± 0.03 | 1.10 ± 0.04 | 0.99 ± 0.02 | 1.00 ± 0.02 | 0.99 ± 0.02 |
400 k | 1.09 ± 0.06 | 0.89 ± 0.04 | 1.07 ± 0.04 | 0.99 ± 0.02 | 0.99 ± 0.01 | 0.99 ± 0.02 |
200 k | 1.14 ± 0.06 | 0.89 ± 0.06 | 1.04 ± 0.05 | 0.98 ± 0.02 | 1.00 ± 0.02 | 0.98 ± 0.03 |
100 k | 1.08 ± 0.08 | 0.85 ± 0.06 | 1.06 ± 0.05 | 0.98 ± 0.03 | 0.99 ± 0.03 | 0.98 ± 0.03 |