Contents
MCODE is a Cytoscape plugin that finds clusters (highly interconnected regions) in a network. Clusters mean different things in different types of networks. For instance, clusters in a protein-protein interaction network are often protein complexes and parts of pathways, while clusters in a protein similarity network represent protein families. Cytoscape is freely available network visualization and analysis software.
Coming Soon: Run MCODE v1.3 using Java WebStart
MCODE is a relatively fast method of clustering. With an intuitive interface, it is suited for both computationally and biologically oriented researchers. Current features include:
- Fast network clustering
- Fine-tuning of results with numerous node-scoring and cluster-finding parameters
- Interactive cluster boundary and content exploration
- Multiple result set management
- Cluster sub-network creation and plain text export
Currently, MCODE does not provide any statistical score on the resulting clusters but can be used as a discovery tool in network analysis. Please see the MCODE paper for more information. Also be sure to consult the documentation for screen shots, descriptions, and tutorials.
Latest Download
The current MCODE Cytoscape plugin is MCODE v1.3.
With Cytoscape 2.5.1 (or later), you can download the latest MCODE version directly from within the software using the Plugin Manager (Plugins > Manage Plugins). MCODE is found under the Analysis category.
Otherwise, you may install the plugin manually: Download the latest version
Plugin requires Cytoscape v2.5.1 or later and Java 1.5.0
See the documentation for installation instructions
Previous Versions
MCODE v1.2
- requires Cytoscape v2.3 to v2.4
MCODE v1.1
- requires Cytoscape v2.1
MCODE v1.0
- requires Cytoscape v2.0
Literature and Resources
MCODE Publication
Please see the following paper for more information about the algorithm:
- Bader GD, Hogue CW.
- An automated method for finding molecular complexes in large protein interaction networks.
BMC Bioinformatics. 2003 Jan 13;4(1):2.
Documentation
The MCODE User's Manual is both a great place to start learning the basics and a helpful reference for expert users. It includes installation instructions, explanations, definitions, examples and tutorials to help you produce, interpret, output, and validate results.
Cytoscape Tutorials
A great deal of introductory and advanced tutorials are available at the Cytoscape Tutorial Resource. Section 7: Modules and Complexes incorporates MCODE, and several other plugins, in a complex discovery and validation exercise.
Future Developments
- Ability to run MCODE from the command line
- Automation of
- Robustness tests
- Gene function over-representation analysis
- Benchmarking: result comparison and validation using cluster benchmark
- Attribute-enhanced clustering: consideration of user attributes, like expression data, in the clustering algorithm
Contact
Bugs / Feature Requests
If you encounter a bug with this plugin, or have a feature suggestion, please e-mail Gary Bader. Be sure to take a look at the Future Developments section before e-mailing a feature request.
Collaboration
This software is open-source. If you modify the source code and would like the modification to be included in a subsequent release, we would love to hear from you. Please send me an e-mail to Gary Bader.
Software Development
If you are a software developer, the MCODE algorithm is easy to incorporate into your own Java software. Just download the source code to get started.
- MCODE source code and Javadoc are made available through Subversion (SVN), a version control repository.
SVN Account Access: MCODE directory
Quick-Link: Javadoc
The Cytoscape developer wiki provides some detailed instructions on using SVN: http://cytoscape.org/cgi-bin/moin.cgi/SVN_Access
Credits
Version 1.3 is a Cytoscape compatibility update and was produced in conjunction with Mike Smoot and the Cytoscape development team.
Version 1.2 was produced by Vuk Pavlovic in the Bader Lab. Thanks to Christopher Workman (The Technical University of Denmark) and Carlo Laudanna (University of Verona) for their expert input during beta-testing.
This software was originally released as a command-line-only program from the Hogue Lab. It was created by Gary Bader, currently based in the Bader Lab at the University of Toronto (formerly in the Sander Group, Computational Biology Center, Memorial Sloan-Kettering Cancer Center, New York City)
This software is made available under the LGPL (Lesser General Public License), which means that you can freely use it within your own software, but if you alter the code itself and distribute it, you must make the source code alterations freely available as well.