Table 1 Example 1 - estimation results
From: Mixture SNPs effect on phenotype in genome-wide association studies
Simulation Case 1 | Simulation Case 2 | |||||
|---|---|---|---|---|---|---|
Parameters | ||||||
True value | Estimates from | Estimates from | True value | Estimates from | Estimates from | |
HBM (s.e)a | MLM (s.e)a | HBM (s.e)a | MLM (s.e)a | |||
| 0 | 0.01 (0.06) | 0.03 (0.06) | 0 | 0.02 (0.02) | 0.02 (0.02) |
| 0.1 | 0.11 (0.06) | 0.011 (0.006) | 0.1 | 0.11 (0.05) | 0.012 (0.004) |
| 1 | 0.94 (0.24) | 1.12(0.04) | 1 | 1.03 (0.03) | 1.04 (0.05) |
| 1 | 1.21 (0.13) | 1.19 (0.20) | 1 | 1.13 (0.35) | 1.62 (0.65) |
| 0.01 | 0.007 (0.003) | - | 0.01 | 0.008 (0.002) | - |
PVE c | 0.5 | 0.53 (0.12) | 0.52 (0.21) | 0.5 | 0.52 (0.15) | 0.61 (0.13) b |
Number of Random Effects | 10,000 | |||||
- aValues in parenthesis are standard errors. bGenetic Variance
g
2 is defined in the same way in [11] which equals to 
b
2 ×N. N is the number of SNPs whose effect b
j
follows the 
(0, σ
b
2) distribution. cPVE is calculated as 
.
g
2 is defined in the same way in [
b
2 ×N. N is the number of SNPs whose effect b
j
follows the 
(0, σ
b
2) distribution. cPVE is calculated as 
.