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

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.

05-May-2015: Version 5.0 of the Molecular Signatures Database (MSigDB) is now available. It includes a new collection (H) of 50 hallmark signatures and a number of other additions and updates. See the MSigDB v5.0 Release Notes for details

10-Jun-2014: In collaboration with the Bader Lab at the University of Toronto, we have added Enrichment Map visualizations as one of the steps in a GSEA analysis. See the GSEA v2.1.0 Release Notes for details.

Registration

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.

Contributors

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).