A GPU-accelerated Clustering App for Cytoscape

AllegroMCODE for Cytoscape is a high-performance MCODE cluster finder supporting both of CPU and GPU clustering. Clusters in a protein interaction network can be considered as protein complexes and functional modules, which can be identified as highly interconnected subgraphs.

It finds the same clusters as the MCODE does, but to process large complex networks it is totally redesigned for fast analysis, low memory consumption, and interactive cluster exploring without creating a network view. Its GPU analysis usually takes less than a second even for a large complex network.

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AllegroMCODE v2.1 is available in Cytoscape App Store!

The GPU clustering is only supported by the professional edition, but the free community edition includes the 15-day evaluation of the fully featured professional edition. If you need more time to evaluate the professional edition, please contact us.

Try Free Community Edition

Intuitive User Interface

The AllegroMCODE v2.x App has totally redesigned user interface. The new cluster explorer helps you to navigate clusters interactively and you can select nodes and edges in a found cluster without creating a sub-netowrk and also zoom in/out clusters. This video tutorial shows you how to find cluster and navigate found clusters by using the cluster explorer in the AllegroMCODE result panel.

The analysis task of the MCODE algorithm to find the clusters can be long for large complex networks even though the algorithm is a relatively fast method. The GPU implementation of AllegroMCODE can be hundreds of times faster than the CPU implementation of the MCODE App.

Check out the Performance Charts

Less Working Memory

AllegroMCODE use its own graph data structure which is optimized for memory usage. It uses much less working memory than the MCODE App. In addition, its GPU processing makes the analysis module use the graphics memory as its working memory so that the main memory usage is dramatically reduced.

Efficient Result Management

All of cluster results are internally cached by AllegroMCODE while the MCODE App only caches the last result per network. If you change some algorithm options and do the analysis for a network which has already processed, AllegroMCODE only do the necessary steps and the new result is also cached. If you would like to remove a result in the cache to save the memory, it can be done to discard the result at any time.

You sometimes want to get more appropriate clusters from your networks so that you would like to fine-tune the algorithm options for your needs. However, it could be difficult without understanding how the algorithm works.

This video shows you what the MCODE algorithm is and how it finds clusters in easy-to-understand manner.

  • A travel guide to Cytoscape plugins, Nature Methods, 2012
  • PINA v2.0: mining interactome modules, Nucl. Acids Res., 2012
  • A noise reducing sampling approach for uncovering critical properties in large scale biological networks, High Performance Computing and Simulation (HPCS), 2011 International Conference
  • A GPU-accelerated bioinformatics application for large-scale protein interaction networks, APBC poster presentation, 2011
Learn more about publications & cited papers

How To Install

Please download the plugin jar file at Cytoscape App Store to the “plugins” folder in the Cytoscape or use the “install plugin from file” menu under Cytoscape “plugins” menu.
To use the GPU acceleration on Mac OS, you need to install NVIDIA CUDA Driver For Mac. (For more details, please read the “How to install CUDA Driver on Mac” section in Support>FAQs.)
You can also install Cytoscape v2.8.3 by downloading it from http://www.cytoscape.org/download.html.

System Requirements

Cytoscape Version

  • Cytoscape 2.6, 2.7, 2.8 or later
  • A product for Cytoscape 3.0 will be released soon.The current license holders will be able to use it freely.

Operating System

  • Windows XP, Vista, 7 & 8
  • MAC OS X Snow Leopard, Lion  & Mountain Lion
  • Linux

Supported GPU

  • Any CUDA-capable NVIDIA GPU (Most NVIDIA Graphics Cards Supported)

You can check the CUDA capability Table.

MCODE is the cluster finding algorithm app which is developed by the Bader Lab at the University of Toronto. For more information, visit http://baderlab.org/Software/MCODE.
Cytoscape is a popular network visualization and analysis software and is freely available. You can download Cytoscape and get detailed information from http://www.cytoscape.org.