Overview

Gene Set Enrichment Analysis (GSEA) is a computational method that determines whether an a priori defined set of genes shows statistically
significant, concordant differences between two biological states
(e.g. phenotypes).

From this web site, you can:

What's New

19-Oct-2017: MSigDB 6.1 released. See release notes for more information, including important corrections to gene sets in the C3 collection.

11-Aug-2017: Four new CHIP files are now available for use with data specified with Ensembl IDs, which are commonly used for gene expression derived from RNA-Seq data. More details are here.

01-Jul-2017: The production version of GSEA Desktop v3.0 is now available! It's open-source on GitHub, features SVG plots, Cytoscape 3.3+ support for Enrichment Maps, heatmap dataset export, and more.

06-Apr-2017: Version 6.0 of the Molecular Signatures Database (MSigDB) is now available under a Creative Commons license, with additional terms for some sub-collections of gene sets. The release also includes updates to the C3 motif gene sets, and some other minor additions and corrections. See the Release Notes for details.

06-Oct-2016: Version 5.2 of the Molecular Signatures Database (MSigDB) is now available. It contains the overhauled C5 collection of 6,166 sets of recent gene ontology annotations, as well as a number of additions, updates and corrections. See the Release Notes for details.


License Terms

GSEA and MSigDB are available for use under these license terms.

Please register to download the GSEA software, access our web tools, and view the MSigDB gene sets. After registering, you can log in at any time using your email address. Registration is free. Its only purpose is to help us track usage for reports to our funding agencies.

Contributors

GSEA and MSigDB are maintained by the GSEA team. Our thanks to our many contributors. Funded by: National Cancer Institute, National Institutes of Health, National Institute of General Medical Sciences.

Citing GSEA

To cite your use of the GSEA software, please reference Subramanian, Tamayo, et al. (2005, PNAS 102, 15545-15550) and Mootha, Lindgren, et al. (2003, Nat Genet 34, 267-273).