EXCAVATOR: a computer program for ef®ciently mining gene expression data

Massive amounts of gene expression data are generated using microarrays for functional studies of genes and gene expression data clustering is a useful tool for studying the functional relationship among genes in a biological process. We have developed a computer package EXCAVATOR for clustering gene expression pro®les based on our new framework for representing gene expression data as a minimum spanning tree. EXCAVATOR uses a number of rigorous and ef®cient clustering algorithms. This program has a number of unique features, including capabilities for: (i) dataconstrained clustering; (ii) identi®cation of genes with similar expression pro®les to pre-speci®ed seed genes; (iii) cluster identi®cation from a noisy background; (iv) computational comparison between different clustering results of the same data set. EXCAVATOR can be run from a Unix/Linux/ DOS shell, from a Java interface or from a Web server. The clustering results can be visualized as colored ®gures and 2-dimensional plots. Moreover, EXCAVATOR provides a wide range of options for data formats, distance measures, objective functions, clustering algorithms, methods to choose number of clusters, etc. The effectiveness of EXCAVATOR has been demonstrated on several experimental data sets. Its performance compares favorably against the popular K-means clustering method in terms of clustering quality and comput-