Table 1 Summary of the scenarios used in the simulations
From: Bayesian neural networks with variable selection for prediction of genotypic values
| Â | #QTL | Explanation | Var(A) | Var(D) | Var(E) |
|---|---|---|---|---|---|
Base | 300 | Default scenario | 1.0 | 0.0 | 0.0 |
\(S_{10}\) | 10 | Very sparse | 1.0 | 0.0 | 0.0 |
\(S_{100}\) | 100 | Sparse | 1.0 | 0.0 | 0.0 |
\(S_{1000}\) | 1000 | Dense | 1.0 | 0.0 | 0.0 |
\(D_{\text {medium}}\) | 300 | Medium dominance | 0.854 | 0.161 | 0.0 |
\(D_{\text {extreme}}\) | 300 | Extreme dominance | 0.636 | 0.386 | 0.0 |
\(E_{A}\) | 300 | Additive \(\times\) additive epistasis | 0.657 | 0.0 | 0.366 |
\(E_{C}\) | 300 | Complementary epistasis | 0.658 | 0.225 | 0.116 |
\(E_{I}\) | 300 | Interaction epistasis | 0.896 | 0.0 | 0.127 |