A new web-based data mining tool for the identification of candidate genes for human genetic disorders

• Published in: European journal of human genetics : EJHG Vol. 11; no. 1; pp. 57 - 63
• Main Authors: VAN DRIEL, Marc A, CUELENAERE, Koen, KEMMEREN, Patrick P. C. W, LEUNISSEN, Jack A. M, BRUNNER, Han G
• Format: Journal Article
• Language: English
• Published: Avenel, NJ Nature Publishing 01.01.2003; Nature Publishing Group
• Subjects: adult-syndrome; Automation; Bioinformatics; Biological and medical sciences; Chromosomes; Computational Biology - methods; Data mining; Data processing; Databases, Genetic; Databases, Nucleic Acid; dysplasia; expression database; Gene Expression; General aspects. Genetic counseling; Genetic Diseases, Inborn - genetics; Genetic disorders; Genetics; Genomes; Genomics; human genome; Humans; Identification; Internet; Kinases; Medical genetics; Medical research; Medical sciences; mouse; Mutation; Noonan Syndrome - genetics; noonan-syndrome; Phenotypes; recessive robinow-syndrome; Researchers; ror2; sequence; Software; United States > US; Netherlands; Human; Biomedical data processing; Gene; Pathogenesis; Database; Exploration; Internet; Genetic determinism; Genetic disease
• ISSN: 1018-4813; 1476-5438
• DOI: 10.1038/sj.ejhg.5200918

To identify the gene underlying a human genetic disorder can be difficult and time-consuming. Typically, positional data delimit a chromosomal region that contains between 20 and 200 genes. The choice then lies between sequencing large numbers of genes, or setting priorities by combining positional data with available expression and phenotype data, contained in different internet databases. This process of examining positional candidates for possible functional clues may be performed in many different ways, depending on the investigator's knowledge and experience. Here, we report on a new tool called the GeneSeeker, which gathers and combines positional data and expression/phenotypic data in an automated way from nine different web-based databases. This results in a quick overview of interesting candidate genes in the region of interest. The GeneSeeker system is built in a modular fashion allowing for easy addition or removal of databases if required. Databases are searched directly through the web, which obviates the need for data warehousing. In order to evaluate the GeneSeeker tool, we analysed syndromes with known genesis. For each of 10 syndromes the GeneSeeker programme generated a shortlist that contained a significantly reduced number of candidate genes from the critical region, yet still contained the causative gene. On average, a list of 163 genes based on position alone was reduced to a more manageable list of 22 genes based on position and expression or phenotype information. We are currently expanding the tool by adding other databases. The GeneSeeker is available via the web-interface (http://www.cmbi.kun.nl/GeneSeeker/).