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Bioinformatics Advance Access originally published online on September 1, 2005
Bioinformatics 2005 21(21):3993-3999; doi:10.1093/bioinformatics/bti644
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© The Author 2005. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions{at}oxfordjournals.org
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A new algorithm for comparing and visualizing relationships between hierarchical and flat gene expression data clusterings

Aurora Torrente 1,2,*, Misha Kapushesky 1 and Alvis Brazma 1

1EMBL Outstation—Hinxton, European Bioinformatics Institute Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
2Universidad Carlos III de Madrid Leganés, CP 28911, Madrid, Spain

*To whom correspondence should be addressed.

Motivation: Clustering is one of the most widely used methods in unsupervised gene expression data analysis. The use of different clustering algorithms or different parameters often produces rather different results on the same data. Biological interpretation of multiple clustering results requires understanding how different clusters relate to each other. It is particularly non-trivial to compare the results of a hierarchical and a flat, e.g. k-means, clustering.

Results: We present a new method for comparing and visualizing relationships between different clustering results, either flat versus flat, or flat versus hierarchical. When comparing a flat clustering to a hierarchical clustering, the algorithm cuts different branches in the hierarchical tree at different levels to optimize the correspondence between the clusters. The optimization function is based on graph layout aesthetics or on mutual information. The clusters are displayed using a bipartite graph where the edges are weighted proportionally to the number of common elements in the respective clusters and the weighted number of crossings is minimized. The performance of the algorithm is tested using simulated and real gene expression data. The algorithm is implemented in the online gene expression data analysis tool Expression Profiler.

Availability: http://www.ebi.ac.uk/expressionprofiler

Contact: aurora{at}ebi.ac.uk

Supplementary information: http://www.ebi.ac.uk/microarray/General/Publications/publications.html

Received on June 16, 2005; revised on August 1, 2005; accepted on August 23, 2005

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