Abstract
In the field of cancer, genetic association studies are among the most active and well-funded research areas, and have produced hundreds of genetic associations, especially in the genome-wide association studies (GWAS) era. Knowledge synthesis of these discoveries is the first critical step in translating the rapidly emerging data from cancer genetic association research into potential applications for clinical practice. To facilitate the effort of translational research on cancer genetics, we have developed a continually updated database named Cancer Genome-wide Association and Meta Analyses database that contains key descriptive characteristics of each genetic association extracted from published GWAS and meta-analyses relevant to cancer risk. Here we describe the design and development of this tool with the aim of aiding the cancer research community to quickly obtain the current updated status in cancer genetic association studies.
Similar content being viewed by others
Log in or create a free account to read this content
Gain free access to this article, as well as selected content from this journal and more on nature.com
or
References
Panoutsopoulou K, Zeggini E : Finding common susceptibility variants for complex disease: past, present and future. Brief Funct Genomic Proteomic 2009; 8: 345–352.
Ioannidis JP, Gwinn M, Little J : A road map for efficient and reliable human genome epidemiology. Nat Genet 2006; 38: 3–5.
Hardy J, Singleton A : Genomewide association studies and human disease. N Engl J Med 2009; 360: 1759–1768.
Khoury MJ, Bertram L, Boffetta P et al: Genome-wide association studies, field synopses, and the development of the knowledge base on genetic variation and human diseases. Am J Epidemiol 2009; 170: 269–279.
Yu W, Clyne M, Dolan SM et al: GAPscreener: an automatic tool for screening human genetic association literature in PubMed using the support vector machine technique. BMC Bioinformatics 2008; 9: 205.
Yu W, Gwinn M, Clyne M, Yesupriya A, Khoury MJ : A navigator for human genome epidemiology. Nat Genet 2008; 40: 124–125.
Dong LM, Potter JD, White E, Ulrich CM, Cardon LR, Peters U : Genetic susceptibility to cancer: the role of polymorphisms in candidate genes. JAMA 2008; 299: 2423–2436.
Yu W, Clyne M, Khoury MJ, Gwinn M : Phenopedia and genopedia: disease-centered and gene-centered views of the evolving knowledge of human genetic associations. Bioinformatics 2010; 26: 145–146.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Competing interests
The authors declare no conflict of interest.
Additional information
Disclaimer
The findings and conclusions in this report are those of the authors and do not necessarily reflect the views of the Department of Health and Human Services.
Rights and permissions
About this article
Cite this article
Schully, S., Yu, W., McCallum, V. et al. Cancer GAMAdb: database of cancer genetic associations from meta-analyses and genome-wide association studies. Eur J Hum Genet 19, 928–930 (2011). https://doi.org/10.1038/ejhg.2011.53
Received:
Revised:
Accepted:
Published:
Issue date:
DOI: https://doi.org/10.1038/ejhg.2011.53
Keywords
This article is cited by
-
A systematic review of cancer GWAS and candidate gene meta-analyses reveals limited overlap but similar effect sizes
European Journal of Human Genetics (2014)
-
Phenotype–Genotype Integrator (PheGenI): synthesizing genome-wide association study (GWAS) data with existing genomic resources
European Journal of Human Genetics (2014)