OrthoClusterDB: An Online Platform for Synteny Blocks

Peer reviewed: 
Yes, item is peer reviewed.
Scholarly level: 
Faculty/Staff
Final version published as: 

BMC Bioinformatics 2009, 10:192 doi:10.1186/1471-2105-10-192

Date created: 
2009
Abstract: 

Background: The recent availability of an expanding collection of genome sequences driven bytechnological advances has facilitated comparative genomics and in particular the identification ofsynteny among multiple genomes. However, the development of effective and easy-to-use methodsfor identifying such conserved gene clusters among multiple genomes–synteny blocks–as well asdatabases, which host synteny blocks from various groups of species (especially eukaryotes) andalso allow users to run synteny-identification programs, lags behind.Descriptions: OrthoClusterDB is a new online platform for the identification and visualization ofsynteny blocks. OrthoClusterDB consists of two key web pages: Run OrthoCluster and View Synteny.The Run OrthoCluster page serves as web front-end to OrthoCluster, a recently developed programfor synteny block detection. Run OrthoCluster offers full control over the functionalities ofOrthoCluster, such as specifying synteny block size, considering order and strandedness of geneswithin synteny blocks, including or excluding nested synteny blocks, handling one-to-manyorthologous relationships, and comparing multiple genomes. In contrast, the View Synteny page givesaccess to perfect and imperfect synteny blocks precomputed for a large number of genomes,without the need for users to retrieve and format input data. Additionally, genes are cross-linkedwith public databases for effective browsing. For both Run OrthoCluster and View Synteny, identifiedsynteny blocks can be browsed at the whole genome, chromosome, and individual gene level.OrthoClusterDB is freely accessible.Conclusion: We have developed an online system for the identification and visualization ofsynteny blocks among multiple genomes. The system is freely available at http://genome.sfu.ca/orthoclusterdb/.

Language: 
English
Document type: 
Article
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