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Bioinformatics Advance Access published online on July 15, 2008
Bioinformatics, doi:10.1093/bioinformatics/btn357
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© 2008 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

PathCluster: a framework for gene set-based hierarchical clustering

Tae-Min Kim 1, Seon-Hee Yim 2, Yong-Bok Jeong 2, Yu-Chae Jung 1 and Yeun-Jun Chung 1,2,*

1Department of Microbiology and 2Integrated Research Center for Genome Polymorphism, College of Medicine, The Catholic University of Korea, Seoul 137-701, Korea

*To whom correspondence should be addressed. Dr. Yeun-Jun Chung, E-mail: yejun{at}catholic.ac.kr


  Abstract

Motivation: Gene clustering and gene set-based functional analysis are widely used for the analysis of expression profiles. The development of a comprehensive method jointly combining the two methods would allow for greater biological insights.

Results: We developed a software package, PathCluster for gene set-based clustering via an agglomerative hierarchical clustering algorithm. The distances between predefined gene sets are illustrated in a dendrogram in which the relationships between gene sets can be visually assessed. Valuable biological insights can be obtained according to the type of gene sets, e.g. coordinated action of molecular functions (functional gene sets) and putative motif syn-ergy (promoter gene set) in a biological process. The combined use of gene sets further enables the interrogation of different biological themes and their putative relationships, such as function-versus-regulatory motif or drug-versus-function. PathCluster can also be used for knowledge-based sample partitioning or class categoriza-tion for clinical purposes. With extended applicability, PathCluster will facilitate the gleaning of meaningful biological insights and test-able hypotheses in the contexts of given expression profiles.

Availability: PathCluster executable files can be freely downloaded at http://www.systemsbiology.co.kr/PathCluster/.

Contact: yejun{at}catholic.ac.kr

Associate Editor: Dr. Olga Troyanskaya

Received on March 4, 2008; revised on June 4, 2008; accepted on July 11, 2008

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