Fig. 2

ClinPrior performance benchmarking in a synthetic cohort. A Variant prioritization performance through the area under the receiver operating characteristic curve (AUROC) in the identification of known disease genes and candidate disease genes (A). ROC curves computed using the patient HPO terms, random HPO terms and random final ClinPrior prioritization rank in the 66,800 synthetic WES analysed. B The method identifies the gene that best matches the patient’s phenotype based on known HPO-gene associations and the propagation of the phenotypic metrics in the multilayer interactome. When the identified gene is a novel candidate gene not previously linked to disease, there are no HPO-gene associations in the phenotypic layer. For benchmarking, we simulated a candidate gene by removing the HPO-Gene associations from each candidate