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Bioinformatics Advance Access originally published online on November 30, 2004
Bioinformatics 2005 21(8):1592-1595; doi:10.1093/bioinformatics/bti169
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© The Author 2004. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions{at}oupjournals.org

Generalized Venn diagrams: a new method of visualizing complex genetic set relations

Hans A. Kestler 1,2,*,{dagger}, André Müller 2,{dagger}, Thomas M. Gress 2,{ddagger} and Malte Buchholz 2,{ddagger}

1Neuroinformatics, University of Ulm 89069 Ulm, Germany
2Internal Medicine I, University Hospital Ulm Robert-Koch-Strasse 8, 89081 Ulm, Germany

*To whom correspondence should be addressed.

Motivation: Microarray experiments generate vast amounts of data. The unknown or only partially known functional context of differentially expressed genes may be assessed by querying the Gene Ontology database via GOMiner. Resulting tree representations are difficult to interpret and are not suited for visualization of this type of data. Methods are needed to effectively visualize these complex set relationships.

Results: We present a visualization approach for set relationships based on Venn diagrams. The proposed extension enhances the usual notion of Venn diagrams by incorporating set size information. The cardinality of the sets and intersection sets is represented by their corresponding circle (polygon) sizes. To avoid local minima, solutions to this problem are sought by evolutionary optimization. This generalized Venn diagram approach has been implemented as an interactive Java application (VennMaster) specifically designed for use with GOMiner in the context of the Gene Ontology database.

Availability: VennMaster is platform-independent (Java 1.4.2) and has been tested on Windows (XP, 2000), Mac OS X, and Linux. Supplementary information and the software (free for non-commercial use) are available at http://www.informatik.uni-ulm.de/ni/mitarbeiter/HKestler/vennm together with a user documentation.

Contact: hans.kestler{at}medizin.uni-ulm.de


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