VisHiC—hierarchical functional enrichment analysis of microarray data

Measuring gene expression levels with microarrays is one of the key technologies of modern genomics. Clustering of microarray data is an important application, as genes with similar expression profiles may be regulated by common pathways and involved in related functions. Gene Ontology (GO) analysis...

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Bibliographic Details
Published in:	Nucleic acids research Vol. 37; no. suppl-2; pp. W587 - W592
Main Authors:	Krushevskaya, Darya, Peterson, Hedi, Reimand, Jüri, Kull, Meelis, Vilo, Jaak
Format:	Journal Article
Language:	English
Published:	England Oxford University Press 01-07-2009 Oxford Publishing Limited (England)
Subjects:	Algorithms Cardiovascular Diseases - genetics Cardiovascular Diseases - metabolism Cluster Analysis Computer Graphics Extracellular Matrix - metabolism Gene Expression Profiling - methods Humans Mitochondria - metabolism Myocardium - metabolism Oligonucleotide Array Sequence Analysis - methods Software
Online Access:	Get full text
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Summary:	Measuring gene expression levels with microarrays is one of the key technologies of modern genomics. Clustering of microarray data is an important application, as genes with similar expression profiles may be regulated by common pathways and involved in related functions. Gene Ontology (GO) analysis and visualization allows researchers to study the biological context of discovered clusters and characterize genes with previously unknown functions. We present VisHiC (Visualization of Hierarchical Clustering), a web server for clustering and compact visualization of gene expression data combined with automated function enrichment analysis. The main output of the analysis is a dendrogram and visual heatmap of the expression matrix that highlights biologically relevant clusters based on enriched GO terms, pathways and regulatory motifs. Clusters with most significant enrichments are contracted in the final visualization, while less relevant parts are hidden altogether. Such a dense representation of microarray data gives a quick global overview of thousands of transcripts in many conditions and provides a good starting point for further analysis. VisHiC is freely available at http://biit.cs.ut.ee/vishic.
Bibliography:	ArticleID:gkp435 ark:/67375/HXZ-FK9P50MV-S istex:B828ED6E30DDBCF5866CE09584813E978BBD7847 ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	0305-1048 1362-4962
DOI:	10.1093/nar/gkp435