Enrichment Map: A Network-Based Method for Gene-Set Enrichment Visualization and Interpretation
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Abstract
BACKGROUND: Gene-set enrichment analysis is a useful technique to help functionally characterize large gene lists, such as the results of gene expression experiments. This technique finds functionally coherent gene-sets, such as pathways, that are statistically over-represented in a given gene list. Ideally, the number of resulting sets is smaller than the number of genes in the list, thus simplifying interpretation. However, the increasing number and redundancy of gene-sets used by many current enrichment analysis software works against this ideal. PRINCIPAL FINDINGS: To overcome gene-set redundancy and help in the interpretation of large gene lists, we developed "Enrichment Map", a network-based visualization method for gene-set enrichment results. Gene-sets are organized in a network, where each set is a node and edges represent gene overlap between sets. Automated network layout groups related gene-sets into network clusters, enabling the user to quickly identify the major enriched functional themes and more easily interpret the enrichment results. CONCLUSIONS: Enrichment Map is a significant advance in the interpretation of enrichment analysis. Any research project that generates a list of genes can take advantage of this visualization framework. Enrichment Map is implemented as a freely available and user friendly plug-in for the Cytoscape network visualization software (http://baderlab.org/Software/EnrichmentMap/).
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The record
- Venue
- PLoS ONE
- Topic
- Bioinformatics and Genomic Networks
- Field
- Biochemistry, Genetics and Molecular Biology
- Canadian institutions
- University of Toronto
- Funders
- National Human Genome Research InstituteNational Institutes of HealthHospital for Sick ChildrenGenome CanadaOntario GenomicsOntario Genomics InstituteHeart and Stroke Foundation of Canada
- Keywords
- VisualizationComputer scienceRedundancy (engineering)Gene regulatory networkSet (abstract data type)Data miningSoftwareGene expression profilingGeneComputational biologyBiologyGeneticsGene expressionProgramming language
- Has abstract in OpenAlex
- yes