The RBVI is pleased to announce the release of clusterMaker 1.10.  This
version of clusterMaker includes several new clustering algorithms,
including k-medoid and the addition of an iterative approach to finding
the best k for k-medoid and k-means using silhouette.  We've also added
the ability to create correlation networks from a set of node
attributes.  This can be used, for example, to create expression
correlation networks from expression data.  With these, clusterMaker now
provides 12 cluster algorithms, three poster-cluster filters, and
several visualizations which tie cluster results into the network,
including the ability to create nodeCharts if the nodeCharts plugin is
installed.

In addition, clusterMaker, now exports a variety of CyCommands, which
can be used from scripts or from other plugins.  clusterMaker
documentation is available at
http://www.cgl.ucsf.edu/cytoscape/cluster/clusterMaker.html and a
manuscript describing three clusterMaker scenarios has just been
published in BMC Bioinformatics: /clusterMaker: a multi-algorithm
clustering plugin for Cytoscape/*. *Morris, JH et al. /BMC
Bioinformatics/ 2011, *12*:436(9 November 2011).  Tutorials describing
those scenarios are also available at
http://opentutorials.cgl.ucsf.edu/index.php/Portal:Cytoscape.

clusterMaker 1.10 is available for download from the Plugin Manager
under the Analysis category.  Please cite the BMC Bioinformatics paper
above if you use clusterMaker.

clusterMaker attribute algorithms:
     AutoSOME Clustering*
     Create Correlation Network from Node Attributes
     Hierarchical cluster
     K-Means cluster**
     K-Medoid cluster**

clusterMaker network partition algorithms:
     Affinity Propagation cluster
     AutoSOME Clustering*
     Connected Components cluster
     Community cluster (GLay)
     MCODE cluster
     MCL cluster*
     SCPS cluster
     Transitivity Clustering*

clusterMaker filters:
     Cutting Edge Filter
     Density Filter
     HairCut Filter

clusterMaker visualizations:
     Create New Network from Attribute
     Create New Network from Clusters
     Create New Network with nested networks from attribute
     Eisen KnnView
     Eisen TreeView
     HeatMapView (unclustered)

* Multi-threaded
** Can use silhouette to estimate k.  Silhouette estimation is
multi-threaded.