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Bioinformatics Advance Access published online on February 13, 2009
Bioinformatics, doi:10.1093/bioinformatics/btp086
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© 2009 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

CGAS: Comparative genomic analysis server

Masumi Itoh and Hidemi Watanabe *

Graduate School of Information Science and Technology, Hokkaido University, Sapporo, Hokkaido, 060-0814, Japan

*To whom correspondence should be addressed. Hidemi Watanabe, E-mail: watanabe{at}ist.hokudai.ac.jp


  Abstract

Summay: Comparative approach is one of the most essential methods for extracting functional and evolutionary information from genomic sequences. So far, a number of sequence comparison tools have been developed, and most are either for on-site use, requiring program installation but providing a wide variety of analyses, or for the online search of user's sequences against given databases on a server. We newly devised an asynchronous JavaScript and XML (Ajax)-based system for comparative genomic analyses, CGAS, with highly interactive interface within a browser, requiring no software installation. The current version, CGAS version 1, provides functionality for viewing similarity relationships between user's sequences, including a multiple dot plot between sequences with their annotation information. The scrollbar-less, "draggable" interface of CGAS is implemented with Google Maps API version 2. The annotation information associated with the genomic sequences compared is synchronously displayed with the comparison view. The multiple-comparison viewer is one of the unique functionalities of this system to allow the users to compare the differences between different pairs of sequences. In this viewer, the system tells orthologous correspondences between the sequences compared interactively. This web-based tool is platform-independent and will provide biologists having no computational skills with opportunities to analyze their own data without software installation and customization of the computer system.

Availability and Implementation: CGAS is available at http://cgas.ist.hokudai.ac.jp/.

Contact: watanabe{at}ist.hokudai.ac.jp

Associate Editor: Dr. Alex Bateman

Received on September 30, 2008; revised on February 10, 2009; accepted on February 11, 2009

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