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#acl All:read |
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#acl All:read | ## IMPORTANT EDITING NOTE (by Daniele Merico, 12/10/2010) ## - links to this page and its subsection have been included in a book chapter ## - if the URL of this page needs to be changed, please keep the current URL and auto-direct to the new one |
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Updated at 07/20/2010 | Updated at 11/16/2010 |
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* [[attachment:EnrichmentMapPlugin_v1.00-RC7.zip|Enrichment Map Plugin (v1.00 Release Candidate 7)]] | * [[attachment:EnrichmentMapPlugin_v1.0.zip|Enrichment Map Plugin (v1.0 Release)]] |
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Distributions with source code: * [[attachment:EnrichmentMapPlugin_v1.0_src.zip|Enrichment Map Plugin with source code (v1.0 Release)]] * [[attachment:EnrichmentMapPlugin_v1.0_src.tar.gz|Enrichment Map Plugin with source code, tar and gzipped (v1.0 Release)]] |
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Estradiol-treated MCF7 breast cancer cells, 12hrs and 24hrs: [[attachment:EM_EBC_TestData.zip]] | === Main analysis === * Estradiol-treated MCF7 cells, 12 and 24hrs (Gene Expression Omnibus: GSE11352) * ''GSEA format:'' * files: [[attachment:EM_EstrogenMCF7_TestData.zip]] * [[Software/EnrichmentMap/Tutorial|Guided tutorial]] to load the files into Enrichment Map * ''Generic format:'' * files: [[attachment:EM_EstrogenMCF7_TestData_Generic.zip]] * note: the results should be the same as GSEA |
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* [[Software/EnrichmentMap/Tutorial|Guided tutorial]] to load the test data into Enrichment Map |
=== Query-set analysis (aka Post-analysis) === * [[attachment:estrogenTargetsLin2007.GMT|Estrogen targets]] (Lin CY et al 2007, Plos Genetics; PMID: 17542648) |
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== Gene-sets for Enrichment Analysis == * we generate gene-set files for enrichment analysis (e.g. GSEA) by querying public resources such as Gene Ontology and KEGG, and using Entrez-Gene ID for genes [[GeneSetDB_02|download page]] * how to convert DAVID gene-sets to GMT: [[/DAVIDgs_R|R script]] |
Enrichment Map Plugin Download Page
Brief Description
Enrichment Map is a Cytoscape plugin for functional enrichment visualization. Enrichment results have to be generated outside Enrichment Map, using any of the available methods. Gene-sets, such as pathways and Gene Ontology terms, are organized into a network (i.e. the "enrichment map"). In this way, mutually overlapping gene-sets cluster together, making interpretation easier. Enrichment Map also enables the comparison of two different enrichment results in the same map.
Follow this link for more details and an analysis example.
Plugin Download
Updated at 11/16/2010
Download the zipped file, move it to the Cytoscape plugin directory and unzip it.
Distributions with source code:
Sample Data Download
Main analysis
- Estradiol-treated MCF7 cells, 12 and 24hrs (Gene Expression Omnibus: GSE11352)
GSEA format:
files: EM_EstrogenMCF7_TestData.zip
Guided tutorial to load the files into Enrichment Map
Generic format:
- note: the results should be the same as GSEA
Query-set analysis (aka Post-analysis)
Estrogen targets (Lin CY et al 2007, Plos Genetics; PMID: 17542648)
User Guide
Gene-sets for Enrichment Analysis
- we generate gene-set files for enrichment analysis (e.g. GSEA) by querying public resources such as Gene Ontology and KEGG, and using Entrez-Gene ID for genes
how to convert DAVID gene-sets to GMT: R script
Publications
Isserlin R, Merico D, Alikhani-Koupaei R, Gramolini A, Bader GD, Emili A.
Pathway analysis of dilated cardiomyopathy using global proteomic profiling and enrichment maps.
Proteomics. 2010 Feb 1.
PMID: 20127684