Database management systems
A database is the most functional, versatile and most recommended tool for the collection and storage of gene variation information . A database management system provides the underlying software on which a gene/disease specific database is run and provides a means for the submission, storage, maintenance, and distribution of data, as well as managing security and other functions required for database use .
Database Management systems and interface functionality
It is recommended that the database management system [3,4]:
- Has the ability to record the information in a comprehensive and easy to use style .
- User-friendly Web pages
- Easy to use search and navigate capabilities
- Consistency and clarity of design and graphics 
- Allows secure, modifiable and permanent data storage
- Incorporates mechanisms for sharing of data between repositories 
- Ability to integrate with existing technologies and external software tools, for improved database utilisation.
The database design should meet the requirements and objectives of the individual database.
It is recommended to use a an existing database management system that has been specifcially designed for gene/disease specific databases .
Possible solutions include:
The Leiden Open Variation Database (LOVD) is a specific software developed in collaboration with HVP to standardise data recording, accurately and easily collect and maintain data on genetic variations causing disease and other genetic variants . More information can be found at the LOVD website and in the LOVD Manual.
- 1.Human Variome Project. Project Roadmap 2012-2016. 2012.
- 2.Royal College of Pathologists of Australia. Standards for clinical databases of genetic variants. 2014.
- 3.Vihinen, M., Dunnen, J.T. den, Dalgleish, R., and Cotton, R.G.H. Guidelines for establishing locus specific databases. Human Mutation 33, 2 (2012), 298–305.
- 4. Human Variome Project Working Group WG05: Variant Database Quality Assessment. HVP Guideline: Gene/Disease Specific Variant Database Quality Parameters. .
- 5.Patrinos, G.P., Al Aama, J., Al Aqeel, A., et al. Recommendations for genetic variation data capture in developing countries to ensure a comprehensive worldwide data collection. Human Mutation 32(1):2-9. Human Mutation 32, 1 (2011), 2–9.
- 6.Mitropoulou, C., Webb, A.J., Mitropoulos, K., Brookes, A.J., and Patrinos, G.P. Locus-specific database domain and data content analysis: evolution and content maturation toward clinical use. Human Mutation 31, 10 (2010), 1109–1116.
- 7.Fokkema, I.F.A.C., Taschner, P.E.M., Schaafsma, C.P., G, Celli, J., Laros, J.F.J., and Dunnen J.T., den. LOVD v.2.0: the next generation in gene variant databases. Human Mutation 32, 5 (2011), 557–563.