Scientific Evidence Based Genetic Testing Ontology Development towards Individualized Medicine

Lack of intelligent genetic testing recommendation systems that leverage a high volume of information regarding to available genetic tests, impedes widely incorporating genetic tests into regular clinical practice to further improve healthcare and reduce health cost. To fill this gap, we introduced an integrative genetic testing relevant resource called Genetic Testing Ontology (GTO), which is the first step to develop a genetic testing recommendation system, iGenetics. More specifically, we integrated multiple well-known genetic testing relevant resources, including Genetic Testing Registry (GTR), ClinVar and Human Phenotype Ontology (HPO) and formally represented it by usingWeb Ontology Language (OWL). A meta-ontology has been designed to capture semantics upon the nature of the selected data via Protégé. The GTO was built on top of the meta-ontology subsequently by populating specific genetic testing data. In addition, literature data from SemMedDB has been extracted and integrated into the GTO to provide scientific evidence accordingly. We performed one case study to further evaluate the GTO and demonstrate the usability of the GTO.