Given the summary statistics and ancestry-matched LD reference panel for each discovery sample, the PRS-CSx model can be fitted using a Gibbs sampler with block update of posterior SNP effect sizes, without the need to access individual-level data (Supplementary Note). Monomorphic or rare variants not present in the GWAS summary statistics or population-specific LD reference panel of population A are not included in the construction of PRS for population A. If a SNP is present in population A but is monomorphic or rare in other populations, its effect size is not coupled across populations in posterior inference but the SNP is included in the PRS of population A such that population-specific associations can be captured (Fig. 1). In the extreme, unlikely scenario, where there is no overlapping SNP between input GWAS summary statistics, PRS-CSx reduces to applying PRS-CS separately to each discovery GWAS. PRS-CSx inherits many features from PRS-CS, including robustness to varying genetic architectures, multivariate modeling of population-specific LD patterns, and computational efficiency. In this work, we used pre-calculated 1KG Phase 3 LD reference panels43 for EUR, EAS, AFR
