Due to distinct allele frequencies and LD structures across populations, risk prediction accuracy usually drops when the training and testing samples are from different populations. In order to investigate the robustness of AnnoPred against population heterogeneity, we applied AnnoPred to three non-European cohorts for breast cancer and type-II diabetes while training the model using summary statistics from European-based studies. The CORs and AUCs are summarized in S6 and S7 Tables. As expected, we observed a drop in prediction accuracy for all methods. However, AnnoPred still performed the best in all three trans-ethnic validation datasets.
