LRRK2 and Parkinson disease: The model trained on tile deep embeddings achieved a 0.77 (0.10 SD) ROC AUC for separating sporadic PD from controls and 0.89 (0.10 SD) ROC AUC for separating LRRK2 PD from controls (Fig. 5c, d), indicating that both patient groups contain strong disease-specific signatures.