Bioinformatics Advance Access originally published online on June 30, 2005
Bioinformatics 2005 21(17):3580-3581; doi:10.1093/bioinformatics/bti560
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TO-GO: a Java-based Gene Ontology navigation environment
1National Genome Information Center, KRIBB Oun 52, Yusong, Daejeon 305-333, Korea
2Department of Bioinformatics and Life Science, Soongsil University Seoul, Korea
*To whom correspondence should be addressed.
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Abstract |
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Summary: TO-GO is a Gene Ontology (GO) navigation tool, which is implemented as a Java application. After the initial data downloading, the GO term tree can be interactively navigated without further network transfer. Local annotation can be incorporated. It supports querying by GO terms or associated gene product information, displaying the result as a table or a sub-tree. The result from the search for a set of external database accessions includes the number of gene products associated with each node, inclusive of sub-nodes. Search results can be further processed by set operations and these set operations can be quite useful for expression profile data analysis. A copy/paste function is also implemented in order to facilitate data exchange between applications.
Availability: TO-GO is freely available at http://www.ngic.re.kr/togo/index.html
Contact: ungsik{at}kribb.re.kr
The Gene Ontology (GO) consortium (Ashburner et al., 2000) is producing a dynamic controlled vocabulary that can be applied to all organisms even as the knowledge of gene and protein roles in cells accumulates and changes. The consortium also provides the associations between gene products and GO terms made by the member organizations (http://www.geneontology.org). As the GO matures, the ontology will play a central role in the biological information integration.
There already exist many tools for browsing annotations and the ontology, such as AmiGO, QuickGO, DAG-Edit and EGO (http://www.geneontology.org/GO.tools.shtml), but these are mostly Web/HTML-based and thereby have inherent limitations in client/server architecture applications. Since all the computations are done in the server, operations such as expanding and collapsing the tree require network traffic between the browser and the server. Inability of handling local annotation information and difficulty of integration with other applications are among the other limitations. GO terms have been extensively used in the gene expression profile analysis (Khatri et al., 2002; Jenssen et al., 2001; Pletcher et al., 2002, http://eb.ebi.ac.uk/EP/GO, http://www.genmapp.org). It will be desirable if sets of genes selected from expression profiling can be located on a GO tree that can be expanded, collapsed and computed on interactively.
We have developed a new Java-based application, which overcomes these limitations. TO-GO is implemented as a Java Swing application that utilizes JTree, JTable and other GUI components. All the required data is read into the application upon program startup and there is no further network data access required. The local annotation information can be incorporated into the application by reading in a file by following the format of the GO annotation guide (http://www.geneontology.org/GO.annotation.shtml). Annotation information on locally maintained clones can be easily integrated into TO-GO, which allows experimenters to search through the GO-tree directly by their own clone IDs without referring to public databases. As all the operations such as searching, expanding and collapsing the GO tree are carried out locally, the response is faster than web-based tools.
TO-GO supports various ways of querying the GO database such as searching by GO id, GO name, GO definition, gene product name and evidence. Multiple value queries can be carried out by specifying each search value line by line. The search can be carried out in exact, wild card and regular expression style match, and the data source and evidence code can be restricted for the selected values. Search results are viewed in a tree form. Figure 1 shows the main screen and a search for caspase.
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Combining search results using set operations such as union, intersection and subtraction is also provided, which is expected to enrich the GO analysis (Fig. 3). For example, one can look for common or specific GO terms mapped by the gene sets obtained from microarray analyses. Furthermore, distinct gene sets identified by different microarray experiments with different type of samples or treatments could be compared to yield biological insights that would not be given easily by a single search result.
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Querying by GO terms or IDs displays the hits in a ‘pruned’ sub-tree showing the hierarchical relationships between the hits (Fig. 2). From this tree, gene product information associated with the GO terms can be listed. It also counts the cumulative number of gene product hits associated with each node (inclusive of its sub-nodes). By expanding and collapsing the tree, the details of gene product classification can be controlled. The search function of TO-GO can use system clipboard to obtain the query input or to save the result. This copy/paste functionality allows convenient data exchange with other applications such as Microsoft Excel, Word and other Java applications.
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We wrap TO-GO as a Java web start application. This technology provides the following advantages over normal Java applet or application. Application codes and data can be packaged into a single jar file, which can be easily deployed using most http servers. After initial download and caching, each invocation checks for updates. If the server-side jar file is updated, the client-side cache is automatically updated. Otherwise the local cache is used. This application uses the monthly XML dump of the GO database (http://archive.godatabase.org/). The download size of the compressed jar file is
10 MB. Access to local services such as system clipboard access and file IO is provided using the Java Network Launching Protocol (JNLP) without the requirement of special security privilege. Accessing cross-referenced web pages using a regular web browser is also implemented.
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Acknowledgments |
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This work was supported by Grant No. M10407010001-04N0701-00110 from the Ministry of Science & Technology, Korea.
Conflict of Interest: none declared.
Received on August 3, 2004; revised on May 31, 2005; accepted on June 27, 2005
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REFERENCES |
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Ashburner, M., et al. (2000) Gene Ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat. Genet., 25, 25–29[CrossRef][ISI][Medline].
Jenssen, T.K., et al. (2001) A literature network of human genes for high-throughput analysis of gene expression. Nat. Genet., 28, 21–28[CrossRef][ISI][Medline].
Khatri, P., et al. (2002) Profiling gene expression using onto-express. Genomics, 79, 266–270[CrossRef][ISI][Medline].
Pletcher, S.D., et al. (2002) Genome-wide transcript profiles in aging and calorically restricted Drosophila melanogaster. Curr. Biol., 12, 712–723[CrossRef][ISI][Medline].
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