wiki:ObservStart

Version 14 (modified by Morris Swertz, 12 years ago) (diff)

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Welcome to Pheno-OM and Pheno-TAB

Pheno-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 data across human genetics, model organisms and biobanks. Next to the object model we have an tabular exchange format Pheno-TAB and user interfaces, search wizard, ontology links and Excel import/export.

Developers

Core of Pheno-OM and Pheno-TAB was developed by:

Applications using Phenoflow are developed by:

Motivation

The next stage of epidemiological and genetic research will depend critically on large collections of high quality samples and data. A wealth of panels from natural human and experimental model organism populations is readily available, but their annotation is scattered between thousands broad inter-institute panel biobanks and deep departmental boutique disease biobanks, each with their own data front-end. While standardization efforts have produced simple formats for the exchange and integration of high throughput data, such as MAGE-TAB for microarrays and XGAP for xQTL studies an equally lightweight system for phenotypic data is still left wanted

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 PhenoFlow model has been picked up to produce:

The most recent sourcecode of all these projects is available from SVN at http://www.molgenis.org/svn/pheno