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<a href="http://www.broadinstitute.org/gsea/">GSEA Home</a> | <a href="http://www.broadinstitute.org/gsea/downloads.jsp">Downloads</a> | <a href="http://www.broadinstitute.org/gsea/msigdb/">Molecular Signatures Database</a> | <a href="http://www.broadinstitute.org/cancer/software/gsea/wiki/index.php/Main_Page">Documentation</a> | <a href="http://www.broadinstitute.org/gsea/contact.jsp">Contact</a>

Use the navigation bar on the left to display documentation on GSEA software, MSigDB database or GSEA/MSigDB web site. If you have comments or questions not answered by the FAQ or the User Guide, contact us: gsea@broadinstitute.org.

Where to start

If you are new to GSEA, see the Tutorial for a brief overview of the software. If you have a question, see the FAQ or the User Guide. The User Guide describes how to prepare data files, load data files, run the gene set enrichment analysis, and interpret the results. It also includes instructions for running GSEA from the command line and a Quick Reference section, which describes each window of the GSEA desktop application.

MSigDB gene sets

Current release of the Molecular Signatures Database (v3.1 MSigDB) contains 8,513 gene sets for use with GSEA. The best source of information about the gene sets is the MSigDB web site.

Please note that gene sets can change their names or become deprecated in subsequent releases of MSigDB. It is thus important to indicate version of MSigDB to fully reference gene sets used in your study.

Software

We provide the following software implementations of the GSEA method:

  • Java desktop application -- Easy-to-use graphical interface that can be run from the Downloads page. The User Guide fully describes this application (referred to as GSEA or GSEA-P).
  • Java jar file -- Command line interface that can be downloaded from the Downloads page. See Command Line Running GSEA from the Command Line in the User Guide for details. This might be useful for analyzing several datasets sequentially, analyzing large datasets, or running analyses on a compute cluster.
  • R-GSEA -- R implementation of GSEA that can be downloaded from the Downloads page. This implementation is intended for experienced computational biologists who want to tweak and play with algorithm. The R-GSEA Readme provides brief instructions and support is limited. Please note that this implementation has not been actively maintained since 2005.
  • Java source code -- Source code and JavaDoc for the Java jar file can be downloaded from the Downloads page. Further information can be found here and in the Release Notes.

Thank you for your interest in GSEA,
The GSEA Team