Seo, J., Shneiderman, B.
April 2003
HCIL-2003-25, CS-TR-4486, UMIACS-TR-2003-55, ISR-TR-2005-68
Motivation: Multidimensional data sets are common in many research areas, including microarray experiment data sets. Genome researchers are using cluster analysis to find meaningful groups in microarray data. However, the high dimensionality of the data sets hinders users from finding interesting patterns, clusters, and outliers. Determining the biological significance of such features remains problematic due to the difficulties of integrating biological knowledge. In addition, it is not efficient to perform a cluster analysis over the whole data set in cases where researchers know the approximate temporal pattern of the gene expression that they are seeking. Results: To address these problems, we add three new features to the Hierarchical Clustering Explorer (HCE): (1) scatterplot ordering methods so that all 2D projections of a high dimensional data set can be ordered according to relevant criteria, (2) a gene ontology browser, coupled with clustering results so that known gene functions within a cluster can be easily studied, (3) a profile search so that genes with a certain temporal pattern can be easily identified. Availability: HCE 2.0 is a PC application written in Microsoft Visual C++. The full application and user's manual of HCE 2.0 with three new features is freely available at http://www.cs.umd.edu/hcil/hce/ for academic or research purposes.
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