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 | 0.46 ± 0.02 | 0.44 ± 0.04 | 0.47 ± 0.03 | 0.77 ± 0.01 | 0.76 ± 0.01 | 0.77 ± 0.01 |
400 k | 0.46 ± 0.02 | 0.43 ± 0.03 | 0.47 ± 0.02 | 0.76 ± 0.01 | 0.76 ± 0.01 | 0.76 ± 0.01 |
200 k | 0.46 ± 0.02 | 0.42 ± 0.04 | 0.47 ± 0.02 | 0.75 ± 0.01 | 0.75 ± 0.01 | 0.75 ± 0.01 |
100 k | 0.45 ± 0.02 | 0.41 ± 0.03 | 0.46 ± 0.03 | 0.74 ± 0.01 | 0.74 ± 0.01 | 0.74 ± 0.01 |
ρ = 0.8 | ||||||
800 k | 0.54 ± 0.04 | 0.57 ± 0.02 | 0.56 ± 0.03 | 0.74 ± 0.02 | 0.75 ± 0.01 | 0.75 ± 0.02 |
400 k | 0.54 ± 0.03 | 0.56 ± 0.03 | 0.55 ± 0.03 | 0.74 ± 0.02 | 0.74 ± 0.02 | 0.74 ± 0.02 |
200 k | 0.54 ± 0.03 | 0.56 ± 0.02 | 0.55 ± 0.03 | 0.73 ± 0.02 | 0.73 ± 0.02 | 0.73 ± 0.02 |
100 k | 0.53 ± 0.03 | 0.52 ± 0.02 | 0.54 ± 0.03 | 0.72 ± 0.02 | 0.72 ± 0.02 | 0.72 ± 0.02 |
b(TBV, GEBV) | ||||||
ρ = 0.2 | ||||||
800 k | 1.14 ± 0.08 | 0.89 ± 0.09 | 1.16 ± 0.09 | 1.07 ± 0.01 | 1.09 ± 0.01 | 1.07 ± 0.01 |
400 k | 1.14 ± 0.09 | 0.91 ± 0.08 | 1.13 ± 0.09 | 1.07 ± 0.01 | 1.09 ± 0.01 | 1.07 ± 0.01 |
200 k | 1.14 ± 0.09 | 0.88 ± 0.08 | 1.14 ± 0.09 | 1.08 ± 0.01 | 1.09 ± 0.01 | 1.08 ± 0.01 |
100 k | 1.15 ± 0.09 | 0.89 ± 0.09 | 1.15 ± 0.09 | 1.09 ± 0.02 | 1.11 ± 0.03 | 1.09 ± 0.02 |
ρ = 0.8 | ||||||
800 k | 1.12 ± 0.11 | 1.00 ± 0.06 | 1.07 ± 0.09 | 1.01 ± 0.02 | 1.00 ± 0.02 | 1.01 ± 0.02 |
400 k | 1.11 ± 0.11 | 1.02 ± 0.07 | 1.08 ± 0.09 | 1.01 ± 0.02 | 1.00 ± 0.02 | 1.01 ± 0.02 |
200 k | 1.12 ± 0.11 | 1.04 ± 0.07 | 1.11 ± 0.09 | 1.01 ± 0.02 | 1.01 ± 0.02 | 1.01 ± 0.02 |
100 k | 1.11 ± 0.11 | 0.99 ± 0.07 | 1.10 ± 0.10 | 1.01 ± 0.02 | 1.01 ± 0.02 | 1.01 ± 0.02 |