PathCluster: a framework for gene set-based hierarchical clustering.
BACKGROUND
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 synergy (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 categorization for clinical purposes. With extended applicability, PathCluster will facilitate the gleaning of meaningful biological insights and testable hypotheses in the contexts of given expression profiles.


BACKGROUND
PathCluster executable files can be freely downloaded at http://www.systemsbiology.co.kr/PathCluster/.
Kim
Tae-Min
TM
Department of Microbiology and Integrated Research Center for Genome Polymorphism, College of Medicine, The Catholic University of Korea, Seoul 137-701, Korea.
Yim
Seon-Hee
SH
Jeong
Yong-Bok
YB
Jung
Yu-Chae
YC
Chung
Yeun-Jun
YJ
D000465:Algorithms; D016000:Cluster Analysis; D003196:Computer Graphics; D020869:Gene Expression Profiling / Q000379:methods*; D005810:Multigene Family / Q000502:physiology*; D012984:Software; D014584:User-Computer Interface