What is ClusterONE?
ClusterONE (Clustering with Overlapping Neighborhood Expansion) is a graph clustering algorithm that is able to handle weighted graphs and readily generates overlapping clusters. Owing to these properties, it is especially useful for detecting protein complexes in protein-protein interaction networks with associated confidence values. ClusterONE is available as a standalone command-line application, or as a plugin to Cytoscape or ProCope.
Detecting protein complexes is central for our understanding of cellular organization and function. Recent developments in experimental procedures, especially the combination of affinity purification and mass spectrometry (AP-MS) have produced protein-protein interaction datasets for several model organisms such as Saccharomyces cerevisiae and Caenorhabditis elegans. The output of these experiments is a weighted graph, where each node represents a protein, each edge represents a possible interaction and the weights labelling the edges represent interaction confidence values.
ClusterONE is a clustering method for protein-protein interaction datasets that takes into account the confidence values and readily generates overlapping clusters. In our experiments, the predicted complexes show better correspondence with the MIPS catalogue of protein complexes than the results of other popular methods including MCODE, MCL and RNSC. Predicted protein complexes that do not match known MIPS complexes also show a high degree of functional homogeneity.
T. Nepusz, H. Yu, and A. Paccanaro
Detecting overlapping protein complexes in protein-protein interaction networks
Nature Methods, vol. 9, pp. 471-472, 2012.
Java archive (1.0)
Cytoscape 2.x plugin manual
Cytoscape 3.x plugin manual
Command line interface
ProCope plugin manual
Datasets and results
Quality score calculation
Get the source code
ClusterONE is open-source. If you are interested in developing it further, feel free to get the source code from GitHub and experiment with it. You will need Git to check out the source code.
Bug reports, feedback
Something’s not working for you? Do you think you found an error? Do you want to contribute to the development of ClusterONE? Contact us!