Figure 1.

PIPs exhibit a higher efficiency in selecting the true signals than the posterior weights in SuSiE PCA

The proportion of correct classified signals using PIPs as cutoff (A) or posterior weights as cutoff (B). The green dots represent sensitivity, i.e., $\mathrm{Pr}\left(\text{PIPs}\ge \text{cutoff}|\text{True}\text{positive}\text{signal}\right)$, and the red dots represent specificity, i.e., $\mathrm{Pr}\left(\text{PIPs}<\text{cutoff}|\text{True}\text{false}\text{signal}\right)$. For consistency and to ensure comparability between PIPs and weights, the weights are normalized to be ranged from 0 to 1.