test our prediction model. The purpose of cross-validation in our study is purely parameter tuning. To select a suitable tuning parameter, we divide the independent testing dataset (individual level genotype and phenotype data) into two equal parts (A and B), and select the tuning parameters by optimizing prediction accuracy on dataset A. We then evaluate prediction accuracy using the remaining half of testing data, i.e. dataset B. Finally, we repeat the analysis one more time by choosing the tuning parameter on dataset B while evaluating the prediction accuracy on dataset A. Results from these two separate analyses are averaged to quantify model performance. For T2D where multiple independent cohorts are available (phs000237 and phs000388), we used an independent cohort for parameter tuning and the other for evaluating performance (S12 Table). The results are consistent with the cross-validation.
