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).

What’s New

06/09/2010: The recent FTP server access problem has been solved.

06/08/2010: We are currently experiencing problems with FTP access to our server and work to bring it back ASAP. For a possible workaround please refer to the Wiki page on Firewall / FTP connection issues.

02/19/2010: We have a new release of GSEA 2.0.6 that fixes the FTP problems that have been experienced recently. Please discontinue use of older versions and use the new version instead.

12/10/2009: Leading Edge Analysis now works correctly in Release GSEA 2.0.5. There are no changes to the algorithm or functionality.

12/07/2009: Release GSEA 2.0.5 of the GSEA java application is now available. The new release has been updated to work on Snow Leopard. There are no changes to the algorithm or functionality. This update requires Java 6 (on all platforms).

Getting Started

A quick tutorial to get you up and running.

Tools and Information

Downloads: Implementations of GSEA plus additional resources to analyze, annotate and interpret enrichment results.

Molecular Signatures Database: A collection of gene sets for use with GSEA software and tools for exploring them.

Documentation: Information on the GSEA software, the GSEA algorithm.

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 is 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).