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Plant Physiology 133:510-516 (2003)
© 2003 American Society of Plant Biologists

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BIOINFORMATICS

wCLUTO: A Web-Enabled Clustering Toolkit1

Matthew D. Rasmussen, Mukund S. Deshpande, George Karypis*, James Johnson, John A. Crow and Ernest F. Retzel

Department of Computer Science and Engineering, University of Minnesota, 4-192 EE/CS, Minneapolis, Minnesota 55455

As structural and functional genomics efforts provide the biological community with ever-broadening sets of interrelated data, the need to explore such complex information for subtle relationships expands. We present wCLUTO, a Web-enabled version of the stand-alone application CLUTO, designed to apply clustering methods to genomic information. Its first application is focused on the clustering transcriptome data from microarrays. Data can be uploaded by the user into the clustering tool, a choice of several clustering methods can be made and configured, and data are presented to the user in a variety of visual formats, including a three-dimensional "mountain" view of the clusters. Parameters can be explored to rapidly examine a variety of clustering results, and the resulting clusters can be downloaded either for manipulation by other programs or to be saved in a format for publication.

www.plantphysiol.org/cgi/doi/10.1104/pp.103.024885.

1 This work was supported in part by the National Science Foundation (award nos. ACI-0133464, CCR-9972519, EIA-9986042, ACI-9982274, DBI-0196197, DBI-9975806, DBI-9872565, DBI-0221524, and EIA-0224424), by the Army High Performance Computing Research Center (contract no. DAAH04-95-C-0008), by the U.S. Department of Agriculture (grant no. SCA 58-3625-8-117) funded by the North Central Soybean Research board and the United Soybean Board, and by the U.S. Department of Agriculture/CSREES/2002-35300-12621.

* Corresponding author; e-mail karypis{at}cs.umn.edu; fax 612-625-0572.

Received April 4, 2003; returned for revision April 27, 2003; accepted June 30, 2003.

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