| Literature DB >> 20650823 |
Sjozef van Baal1, Joël Zlotogora, George Lagoumintzis, Vassiliki Gkantouna, Ioannis Tzimas, Konstantinos Poulas, Athanassios Tsakalidis, Giovanni Romeo, George P Patrinos.
Abstract
National and ethnic mutation databases (NEMDBs) are emerging online repositories, recording extensive information about the described genetic heterogeneity of an ethnic group or population. These resources facilitate the provision of genetic services and provide a comprehensive list of genomic variations among different populations. As such, they enhance awareness of the various genetic disorders. Here, we describe the features of the ETHNOS software, a simple but versatile tool based on a flat-file database that is specifically designed for the development and curation of NEMDBs. ETHNOS is a freely available software which runs more than half of the NEMDBs currently available. Given the emerging need for NEMDB in genetic testing services and the fact that ETHNOS is the only off-the-shelf software available for NEMDB development and curation, its adoption in subsequent NEMDB development would contribute towards data content uniformity, unlike the diverse contents and quality of the available gene (locus)-specific databases. Finally, we allude to the potential applications of NEMDBs, not only as worldwide central allele frequency repositories, but also, and most importantly, as data warehouses of individual-level genomic data, hence allowing for a comprehensive ethnicity-specific documentation of genomic variation.Entities:
Mesh:
Year: 2010 PMID: 20650823 PMCID: PMC3500166 DOI: 10.1186/1479-7364-4-5-361
Source DB: PubMed Journal: Hum Genomics ISSN: 1473-9542 Impact factor: 4.639
Figure 1Outline of the Israeli national and ethnic mutation database (NEMDB). The database has three main components: disease summaries (categorised by religious groups); allele frequency search options, available separately in a public or restricted password-protected (Search +) environment; and genetic laboratories. The database is under the scientific control of a group of curators under the supervision of the Israeli NEMDB National Coordinator, while a dedicated database development and maintenance team oversees the smooth operation of the Israeli NEMDB.
Figure 2Basic features of the . The format and structure of flat files with multiple lines per record is shown, with the 'summaries' (A) and 'search' files (B) used as examples (see text for details). (C) Structure of the flat file with one line per record, used for entering the mutation frequencies. This file consists of the data source file used in the example of Figure 1B. (D) Part of the database administration menu. The administrator is recognised by the PHP script on the basis of his/her IP address. By clicking on the 'admin' box (in the red oval), an additional screen appears at the top of each page. Again, the selected option is highlighted (disorders page for the example shown in Figure 1C), and the administrator can easily modify its contents using simple html language (see text for details).
Features of the national and ethnic mutation database (NEMDBs) generated for the European Commission-funded MEDGENET project.
| NEMDB | URL | Number of records | Search | Year of | References | |||
|---|---|---|---|---|---|---|---|---|
| Disease summaries | Populations/ethnicities | Search | Genetic laboratories | |||||
| Israeli | 476 | 29 | 945 | 17 | Yes | 2006 | 5,6 | |
| Cypriot* | 28 | 3 | 70 | - | Yes | 2005 | 7 | |
| Tunisian | 102 | - | 165 | - | Yes | 2008 | This paper | |
| Lebanese* | 89 | 2 | 130 | - | No | 2007 | 8 | |
| Egyptian | 38 | - | 94 | - | No | 2008 | This paper | |
*The Cypriot and Lebanese NEMDBs were first generated as national mutation frequency databases and have been subsequently upgraded into their current form.
Figure 3Schematic drawing showing the evolution of NEMDBs towards a global national mutation frequency database (eg FINDbase) [11]and a nationwide CGDB, to which data contribution occurs from different institutional CGDBs. In the former case, summary-level data are stored in a central repository, while in the latter case anonymous individual-level data are contributed unidirectionally in a data warehouse and comparatively analysed and queried.
Figure 4Secure data entry screen from a prototype CGDB, where phenotypic and genotypic data are deposited by authorised users.