Phenotero: annotate as you write

Abstract

Controlled vocabularies and ontologies have become a valuable resource for knowledge representation, data integration, and downstream analyses in the biomedical domain. In precision medicine, especially in clinical genetics, the Human Phenotype Ontology (HPO) as well as disease ontologies like the Orphanet Rare Disease Ontology (ORDO) or Medical Subject Headings (MeSH) are often used for deep phenotyping of patients and coding of clinical diagnoses. However, the process of assigning ontology classes (annotating) to patient descriptions is often disconnected from the process of writing patient reports or manuscripts in word processing software such as Microsoft Word or LibreOffice. This additional workload and the requirement to install dedicated software may discourage usage of ontologies for parts of the target audience.\n\nTo improve this situation, we present Phenotero, a freely available and simple solution to annotate patient phenotypes and diseases at the time of writing clinical reports or manuscripts. We adopt Zotero, a well-established, actively developed citation management software to generate a tool which allows to reference classes from ontologies within clinical reports or manuscripts at the time of writing. We expect this approach to decrease the additional workload to a minimum while ensuring high quality associations with ontology classes. Standardised collection of phenotypic information at the time of describing the patient allows for streamlining of clinic workflow, efficient data entry, and will subsequently promote clinical and molecular diagnosis, remove ambiguousness from manuscripts, and allow sharing of anonymised patient phenotype data with ultimate goal of a better understanding of the disease. Thus, we hope that our integrated approach will further promote the usage of ontologies and controlled vocabularies in the clinical setting and in the biomedical domain.