Nucleic Acids Research, 2005, Vol. 33, Database issue D573-D579
© 2005, the authors
Nucleic Acids Research, Vol. 33, Database issue © Oxford University Press 2005; all rights reserved
SIEGE: Smoking Induced Epithelial Gene Expression Database
1 Bioinformatics Program, College of Engineering, Boston University, 44 Cummington Street, Boston, MA 02215, USA and 2 Pulmonary Center and Department of Medicine, Boston University School of Medicine, 715 Albany Street, Boston, MA 02118, USA
* To whom correspondence should be addressed. Tel: +1 617 638 4860; Fax: +1 617 536 8093; Email: vshah{at}bu.edu
Received August 15, 2004; Revised and Accepted September 23, 2004
The SIEGE (Smoking Induced Epithelial Gene Expression) database is a clinical resource for compiling and analyzing gene expression data from epithelial cells of the human intra-thoracic airway. This database supports a translational research study whose goal is to profile the changes in airway gene expression that are induced by cigarette smoke. RNA is isolated from airway epithelium obtained at bronchoscopy from current-, former- and never-smoker subjects, and hybridized to Affymetrix HG-U133A Genechips, which measure the level of expression of 
22 500 human transcripts. The microarray data generated along with relevant patient information is uploaded to SIEGE by study administrators using the database's web interface, found at http://pulm.bumc.bu.edu/siegeDB. PERL-coded scripts integrated with SIEGE perform various quality control functions including the processing, filtering and formatting of stored data. The R statistical package is used to import database expression values and execute a number of statistical analyses including t-tests, correlation coefficients and hierarchical clustering. Values from all statistical analyses can be queried through CGI-based tools and web forms found on the ‘Search’ section of the database website. Query results are embedded with graphical capabilities as well as with links to other databases containing valuable gene resources, including Entrez Gene, GO, Biocarta, GeneCards, dbSNP and the NCBI Map Viewer.
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