Main Page

<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> | Documentation | <a href="http://www.broadinstitute.org/gsea/contact.jsp">Contact</a>

Use the navigation bar on the left to display GSEA documentation. 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

The Molecular Signatures Database (MSigDB) contains more than 5000 gene sets for use with GSEA. The best source of information about the gene sets is the <a href="http://www.broadinstitute.org/gsea/msigdb">MSigDB</a> page.

Software

 GSEA software is distributed in the following ways:

• Desktop application -- Easy-to-use graphical interface that can be run from the <a href="http://www.broadinstitute.org/gsea/downloads.jsp">Downloads</a> 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 <a href="http://www.broadinstitute.org/gsea/downloads.jsp">Downloads</a> page. The  User Guide describes how to run GSEA from the command line. 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 <a href="http://www.broadinstitute.org/gsea/downloads.jsp">Downloads</a> 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.
  

• Java source code -- Source code and JavaDoc for the Java jar file can be downloaded from this page. Links are in the navigation bar to the left.

Thanks for your interest in GSEA,
The GSEA Team