Phenotypic data derived from high content screenings (HCS) is currently annotated using free-text and no dedicated ontology is available to annotate cellular microscopy phenotypes. This is preventing the integration of independent phenotypic datasets, including datasets generated in different biological domains, such as cell lines, mouse tissues and human tissues.
To solve this issue, we have developed the Cellular Microscopy Phenotype Ontology (CMPO), a species neutral ontology for describing general phenotypic observations relating to the whole cell, cellular components, cellular processes and cell populations. CMPO is compatible with related ontology efforts, such as Fission Yeast Phenotype Ontology, Ascomycete Phenotype Ontology and Mammalian Phenotype Ontology, allowing for future cross-species integration of phenotypic data.
CMPO should be used by researchers generating phenotypic data to annotate the phenotypes identified in their screens, and annotation tools such as Zooma are being developed to facilitate and support the semi-automated annotation of phenotypes with CMPO.
Additionally, CMPO could be used in applications to support browsing and searching CMPO-annotated HCS data. Tools are being developed to implement such functionality and work is in progress to embed CMPO in Webmicroscope at FIMM and CellBASE at EMBL.
The following people have contributed to CMPO development:
- Simon Jupp, Gabriella Rustici, James Malone, Tony Burdett and Helen Parkinson, Elixir
- Jan Ellenberg, Tanja Ninkovic, Jean-Karim Heriche, EuroBioImaging
- Frauke Neuff and Philipp Gormanns, Infrafrontiers
- Johan Lundin, BBMRI/EATRIS
In particular, we wish to thank the following collaborators:
Anna Melidoni, Ruth Lovering and Jennifer Rohn (UCL); Beate Neumann (EMBL); Bob Van De Water (U. Leiden); Bram Herpers (OcellO); Claudia Lukas (U. Copenhagen); Greg Pau (Genentech); Sylvia Le Dévédec (LUMC); Thomas Walter (Institut Curie); Wies Roosmalen (U. Twente); and Zvi Kam (Weizmann Institute).
This work is supported by the BioMedBridges project, which is funded by the European Commission within Research Infrastructures of the FP7 Capacities Specific Programme, grant agreement number 284209