Purpose: To improve the accuracy of matching rare genetic diseases based on patient's phenotypes.
Methods: We introduce new methods to prioritize diagnosis of genetic diseases based on integrated semantic similarity (method 1) and ontological overlap (method 2) between the phenotypes expressed by a patient and phenotypes annotated to known diseases.
Results: We evaluated the performance of our methods by two sets of simulated data and one set of patient's data derived from electronic health records. We demonstrated that the two methods achieved significantly improved performance compared with previous methods in correctly prioritizing candidate diseases in all of the three sets. Our methods are freely available as a web application ( https://gddp.
Research: cchmc.org/ ) to aid diagnosis of genetic diseases.
Conclusion: Our methods can capture the diagnostic information embedded in the phenotype ontology, consider all phenotypes exhibited by a patient, and are more robust than the existing methods when phenotypes are incorrectly or imprecisely specified. These methods can assist the diagnosis of rare genetic diseases and help the interpretation of the results of DNA tests.
Keywords: Diagnosis; Human Phenotype Ontology; Mendelian disease.