Extended Data Fig. 4. The effect of different metrics of GD on the correlation between GD and accuracy.

The y-axis $-\mathit{cor}\left(r_i^2,d_i\right)$ is the correlation between the GD and PGS accuracy; a larger correlation means GD has a better prediction of accuracy. The x-axis are different GD metrics: (1) GD based on PCA with varying number of PCs (from J = 1 to J = 20) and (2) GD based on GRM using pruned PCA SNPs only or all SNPs in PGS models. The GRM GD is computed as $d_i\left(\mathrm{GRM}\right)=\sqrt{\frac{1}{K}{\sum }_{k=1}^K{\left(x_i-x_k\right)}^2}$, where $x_i$ is the standardized genotype of $i_{\mathit{th}}$ testing individual and $x_k$ is the standardized genotype of $k_{\mathit{th}}$ training individual.