A sample storage management system for biobanks.
CONCLUSIONS
Establishment of large-scale biobanks of human specimens is essential to conduct molecular pathological or epidemiological studies. This requires automation of procedures for specimen cataloguing and tracking through complex analytical processes. The International Agency for Research on Cancer (IARC) develops a large portfolio of studies broadly aimed at cancer prevention and including cohort, case-control and case-only studies in various parts of the world. This diversity of study designs, structure, annotations and specimen collections is extremely difficult to accommodate into a single sample management system (SMS). Current commercial or academic SMS are often restricted to a few sample types and tailored to a limited number of analytic workflows [Voegele et al. (2007) A laboratory information management system (LIMS) for a high throughput genetic platform aimed at candidate gene mutation screening. Bioinformatics, 23, 2504-2506]. Thus, we developed a system based on a three-tier architecture and relying on an Oracle database and an Oracle Forms web application. Data are imported through forms or csv files, and information retrieval is enabled via multi-criteria queries that can generate different types of reports including tables, Excel files, trees, pictures and graphs. The system is easy to install, flexible, expandable and implemented with a high degree of data security and confidentiality. Both the database and the interface have been modeled to be compatible with and adaptable to almost all types of biobanks.


METHODS
The SMS source codes, which are under the GNU General Public License, and supplementary data are freely available at 'http://www-gcs.iarc.fr/sms.php'


BACKGROUND
Supplementary data are available at Bioinformatics online.
Voegele
C
C
Genetic Cancer Susceptibility Group, International Agency for Research on Cancer (IARC), Lyon, France. voegele@iarc.fr
Alteyrac
L
L
Caboux
E
E
Smans
M
M
Lesueur
F
F
Le Calvez-Kelm
F
F
Hainaut
P
P
D018070:Biological Specimen Banks; D019295:Computational Biology / Q000379:methods*; D016208:Databases, Factual; D006801:Humans; D016247:Information Storage and Retrieval