Biomedical ontology and annotation data have been growing quickly and proven to be useful in many biomedical applications. Important applications of those data include estimating the functional similarity between ontology terms and between annotated biomedical entities, analyzing enrichment for a set of biomedical entities. Many semantic similarity calculation and enrichment analysis methods have been proposed for such applications. Also, a number of tools have been developed on different platforms for semantic similarity calculation, enrichment analysis, and ontology visualization. However, these tools have implemented a small number of the semantic similarity calculation and enrichment analysis methods for a certain type of biomedical ontology. Note that, the methods can be applied to all types of biomedical ontologies.
In this study, we developed a Cytoscape app, named UFO, which unifies most of the semantic similarity measures for between-term and between-entity similarity calculation for all types of biomedical ontologies. Based on the similarity calculation, UFO can calculate the similarity between two sets of entities and weigh imported entity networks as well as generate functional similarity networks. Besides, it can perform enrichment analysis of a set of entities by different methods. Moreover, UFO can visualize structural relationships between ontology terms, annotating relationships between entities and terms, and functional similarity between entities. Finally, we demonstrated the ability of UFO through some case studies on finding best semantic similarity measures for assessing the similarity between human disease phenotypes; constructing biomedical entity functional similarity networks for predicting disease-associated biomarkers; and performing enrichment analysis on a set of similar phenotypes.
Taken together, UFO is expected to be a tool where biomedical ontologies can be exploited for various biomedical applications.