ClueGO: a Cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks - PubMed (original) (raw)
ClueGO: a Cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks
Gabriela Bindea et al. Bioinformatics. 2009.
Abstract
We have developed ClueGO, an easy to use Cytoscape plug-in that strongly improves biological interpretation of large lists of genes. ClueGO integrates Gene Ontology (GO) terms as well as KEGG/BioCarta pathways and creates a functionally organized GO/pathway term network. It can analyze one or compare two lists of genes and comprehensively visualizes functionally grouped terms. A one-click update option allows ClueGO to automatically download the most recent GO/KEGG release at any time. ClueGO provides an intuitive representation of the analysis results and can be optionally used in conjunction with the GOlorize plug-in.
Figures
Fig. 1.
ClueGO example analysis of up- and down-regulated NK cell genes in peripheral blood from healthy human donors. (a) GO/pathway terms specific for upregulated genes. The bars represent the number of genes associated with the terms. The percentage of genes per term is shown as bar label. (b) Overview chart with functional groups including specific terms for upregulated genes. (c) Functionally grouped network with terms as nodes linked based on their kappa score level (≥0.3), where only the label of the most significant term per group is shown. The node size represents the term enrichment significance. Functionally related groups partially overlap. Not grouped terms are shown in white. (d) The distribution of two clusters visualized on network (c). Terms with up/downregulated genes are shown in red/green, respectively. The color gradient shows the gene proportion of each cluster associated with the term. Equal proportions of the two clusters are represented in white.
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References
- Garcia O, et al. GOlorize: a cytoscape plug-in for network visualization with Gene Ontology-based layout and coloring. Bioinformatics. 2007;23:394–396. - PubMed
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