The C Clustering Library consists of a collection of clustering routines that can be used to analyze gene expression data. Routines for hierarchical (pairwise simple, complete, average, and centroid linkage) clustering, k-means and k-medians clustering, and 2D self-organizing maps on a rectangular grid are included.
The GUI program Cluster 3.0, available for
Windows, Mac OS X, and Linux/Unix, provides the easiest access to the clustering methods in the C clustering library. Cluster 3.0 is an enhanced version of the original Cluster/TreeView program, developed by Michael Eisen of Berkeley Lab. A command-line version of Cluster 3.0 is also available.
For Python users, we have developed an extension module to Python that gives access to the routines in the C clustering library.
A similar module is available for Perl.
The routines can also be called directly from other C programs (which is how we developed Cluster 3.0) by using the source code.
The C clustering library and the corresponding Python extension module were released under the Python License. The Perl module was released under the Artistic License. Cluster 3.0 is currently covered by the original Cluster/TreeView license.