Development of bioinformatics resources for display and analysis of copy number and other structural variants in the human genome.
The discovery of an abundance of copy number variants (CNVs; gains and losses of DNA sequences >1 kb) and other structural variants in the human genome is influencing the way research and diagnostic analyses are being designed and interpreted. As such, comprehensive databases with the most relevant information will be critical to fully understand the results and have impact in a diverse range of disciplines ranging from molecular biology to clinical genetics. Here, we describe the development of bioinformatics resources to facilitate these studies. The Database of Genomic Variants (http://projects.tcag.ca/variation/) is a comprehensive catalogue of structural variation in the human genome. The database currently contains 1,267 regions reported to contain copy number variation or inversions in apparently healthy human cases. We describe the current contents of the database and how it can serve as a resource for interpretation of array comparative genomic hybridization (array CGH) and other DNA copy imbalance data. We also present the structure of the database, which was built using a new data modeling methodology termed Cross-Referenced Tables (XRT). This is a generic and easy-to-use platform, which is strong in handling textual data and complex relationships. Web-based presentation tools have been built allowing publication of XRT data to the web immediately along with rapid sharing of files with other databases and genome browsers. We also describe a novel tool named eFISH (electronic fluorescence in situ hybridization) (http://projects.tcag.ca/efish/), a BLAST-based program that was developed to facilitate the choice of appropriate clones for FISH and CGH experiments, as well as interpretation of results in which genomic DNA probes are used in hybridization-based experiments.
Zhang
J
J
The Centre for Applied Genomics and the Program in Genetics and Genomic Biology, The Hospital for Sick Children, Toronto, Ontario, Canada.
Feuk
L
L
Duggan
G E
GE
Khaja
R
R
Scherer
S W
SW
D000465:Algorithms; D002874:Chromosome Mapping; D019295:Computational Biology / Q000379:methods*; D003627:Data Interpretation, Statistical; D030541:Databases, Genetic; D005821:Genetic Techniques; D014644:Genetic Variation; D015894:Genome, Human; D006801:Humans; D020407:Internet; D009693:Nucleic Acid Hybridization; D011381:Programming Languages; D013223:Statistics as Topic; D014584:User-Computer Interface