attachment:MCODELogo.png

MCODE is a [http://cytoscape.org 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. [http://cytoscape.org Cytoscape] is freely available network visualization and analysis software.

• Run using Java WebStart (TODO: create webstart for 1.2)

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 [http://www.biomedcentral.com/1471-2105/4/2 MCODE paper] for more information. Also be sure to consult the [:Software/MCODE/UsersManual: documentation] for screen shots, descriptions, and tutorials.

TableOfContents()

Latest Download

The current MCODE Cytoscape plugin is MCODE v1.2: [attachment:MCODEv1.2.jar Download the latest version]

• Plugin requires [http://www.cytoscape.org/ Cytoscape] v2.3.2 or later and [http://java.sun.com/j2se/1.5.0/index.jsp Java 1.5.0]

• See the [:Software/MCODE/UsersManual: documentation]

Previous Versions

MCODE v1.1

• TODO: provide download of jar and source
  • requires Cytoscape v2.1

MCODE v1.0

• TODO: provide download of jar and source
  • 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.

• http://www.biomedcentral.com/1471-2105/4/2

Documentation

The [:Software/MCODE/UsersManual: 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.

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 [:GaryBader: 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 [:GaryBader: 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.
• TODO: add links to MCODE source in SVN and Fisheye + link to Cytoscape wiki instructions on how to use SVN to download code. Could also add links to Javadoc - the easiest way to do this may be to check the Javadoc into SVN and link to it (not sure if this will work, but you can test it out)

Credits

Version 1.2 was produced by [:VukPavlovic: Vuk Pavlovic] in the Bader Lab.

This software was originally released as a command-line-only program from the Hogue Lab. It was created by [:GaryBader: Gary Bader], currently based in the [:Home:Bader Lab] at the University of Toronto (formerly in the Sander Group, [http://www.cbio.mskcc.org/ Computational Biology Center, Memorial Sloan-Kettering Cancer Center], New York City)

This software is made available under the [http://www.gnu.org/copyleft/lesser.html 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.