Specifically, XGBoost and random forest had the best performance in CKD (average AUC: 0.846); this was followed by gradient boosting and extra trees (average AUC: 0.843 and 0.839, respectively), and some of the most well-established CKD genes (PKD1, PKD2, COL4A1, COL4A3, COL4A4, and COL4A5) ranked in the top 0.2%–0.7% of all genes (Figure S6). Here, COL4A5 is linked to chronic kidney disease.