Three ontologies to define phenotype measurement data

Abstract

Background: There is an increasing need to integrate phenotype measurement data across studies for both human studies and those involving model organisms. Current practices allow researchers to access only those data involved in a single experiment or multiple experiments utilizing the same protocol.

Results: Three ontologies were created: Clinical Measurement Ontology, Measurement Method Ontology and Experimental Condition Ontology. These ontologies provided the framework for integration of rat phenotype data from multiple studies into a single resource as well as facilitated data integration from multiple human epidemiological studies into a centralized repository.

Conclusion: An ontology based framework for phenotype measurement data affords the ability to successfully integrate vital phenotype data into critical resources, regardless of underlying technological structures allowing the user to easily query and retrieve data from multiple studies.

Keywords: ontology; phenotype.

Figure 1

Three ontologies were developed to standardize the three elements of a measurement record: what was measured, how it was measured and under what conditions it was measured.

Figure 2

The Clinical Measurement Ontology is presented in a hierarchical structure with classes lower down a branch being subclasses of those above with an “is_a” relationship.

Figure 3

Each CMO term was created as phenotype domains addressed with appropriate definitions for each term.

Figure 4

The Measurement Method Ontology structure is based on two major branches, “ex vivo” and “in vivo” and the underlying mechanism or technique used in the method.

Figure 5

The Experiment Condition Ontology is structured by type of condition with both “is_a” and “part_of” relationships with links to identifiers found in other ontologies.

Figure 6

The PhenoMiner website.

Figure 7

Example of phenotype measurement data from multiple studies mapped to the three ontologies for clinical measurement, measurement method, and experimental condition.