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

14-Oct-2016: The new beta of the next major GSEA Desktop release is available, with SVG plots, Cytoscape 3.3+ support, heatmap dataset export, and much more.

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.

01-Oct-2016: The issue with the Documentation section of our website has been resolved. Our apologies for any inconvenience.

17-Jun-2016: You can now follow @GSEA_MSigDB on Twitter!

29-Feb-2016: The Sunday 28-Feb-2016 maintenance is complete on the GSEA/MSigDB website. Thanks for your patience!

13-Jan-2016: Version 5.1 of the Molecular Signatures Database (MSigDB) is now available. It includes the addition of 2,962 gene sets to the C7 collection of immunologic signatures, as well as a number of updates and corrections. See the Release Notes for details.

23-Dec-2015: Our paper describing the generation of the Hallmarks collection and examples of its use for GSEA was published in Cell Systems.

10-Dec-2015: We have confirmed that GSEA v2.2.0 and newer are compatible with Java 8 and produce equivalent results. Its use is highly recommended.


Please register to download the GSEA software 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.


GSEA and MSigDB are maintained by the GSEA team with the support of our MSigDB Scientific Advisory Board. 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).