Ontology-Wide Association Study (OWAS) is a method of increasing the statistical power of GWAS. By taking advantage of the structure of an ontology, we can add additional information that was not previously logged. This is done by each node of the ontology inheriting from its sub classes. This results in less specific traits accumulating cases that was only logged in a more specific trait.
On this website we have made available for the user to browse our generated data. Our dataset is from the UK Biobank and consists of the ICD-10 disease data. We have mapped the ICD-10 data to their phenotype with the Human Phenotype Ontology (HPO), by using text mining in literature. We have done this because ICD-10 is not a proper ontology, compared to HPO, and our method is focusing on taking advantage of an ontology structure.
You can start with browsing from the top of each structure, or you can find the disease/phenotype you want in the search list below.
Update: We have only included individuals that consider themselves as white, to reduce unwanted associations that links to the ethnicity of a group instead of the studied trait.