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Welcome to Observ-OM and Observ-TAB
The simple system to format and exchange observation data.
Background
Observ-OM is a model capture 'any' phenotype observation lead by EU-GEN2PHEN. Our mission mission: store individual and summary level observations in a uniform way to enable harmonization and interoperability of phenotypic and genotypic data across human genetics, model organisms and biobanks. Next to the object model we have an tabular exchange format Observ-TAB and user interfaces, search wizard, ontology links and Excel import/export.
Developers
Core of Pheno-OM and Pheno-TAB was developed by:
- UMC Groningen/GCC (Swertz),
- EBI Hinxton/FG (Adamusiak, Parkinson),
- FIMM Helsinki (Muilu) and
- U Leicester (Thorisson, Brookes)
- other members of EU-GEN2PHEN.
Applications using Pheno-OM are developed by:
- NBIC Biobanking for BiobankCatalog and SemanticSearch? (Antonakaki, van Enckevort, Marshall, Swertz),
- LifeLines for BiobankCatalog (Antonakaki, Lops, Swertz)
- BioSHARE for biobank data integration (Chao, Swertz)
- BBMRI-NL for BiobankCatalog and NgsWorkbench (Antonakaki, Swertz)
- U Groningen for AnimalDB (Roos, Boerema, Swertz)
Easy to adopt system
We here report an easy-to-adopt system for the harmonization, integration and search of phenotypic information from experimental and clinical biobanks. The first component is a community created flexible, ontology-enabled model for the uniform representation of any phenotypic data: panels/cohorts, individuals, protocols, observable features and values (Pheno-OM). Then we present a reusable implementation of this model, including a simple tab/excel based data file format (Pheno-TAB) to harmonize, load and share (meta)data on and a ‘database-in-a-box’ (Pheno-DB) for local biobank projects to quickly setup their own phenotype repository or customize it using the MOLGENIS system. As a next step we aim to demonstrate how use of ontologies and semantic methods in this system enable integrated search of vast collections of phenotypic information across investigations, species and even a federated network of PhenoDB installations. Thus we expect PhenoFlow to lower the barriers for phenotypic data flow between biobanks and enables integrated search across panels and species to find larger sample sets and data for the next generation of biomedical studies.
A growing range of applications
Currently the Pheno-OM model has been picked up to produce:
- the reference implementation which is available at http://www.ebi.ac.uk/microarray-srv/pheno (Adamusiak, Parkinson, GEN2PHEN, Swertz)
- the BiobankCatalog by the NBIC Biobanking Task force (Antonakaki, Enckevoort), LifeLines (Lops) and BBMRI-NL (Swertz).
- the AnimalDB database for tracking animal observations (Roos)
- the NGS workbench for tracking all around next generation sequencing experiment by BBMRI-NL (Dijkstra)
The most recent sourcecode of all these projects is available from SVN at http://www.molgenis.org/svn/pheno
