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If you have a question, see the [[FAQ]] or the [http://www.broadinstitute.org/gsea/doc/GSEAUserGuideFrame.html 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. <br />
 
If you have a question, see the [[FAQ]] or the [http://www.broadinstitute.org/gsea/doc/GSEAUserGuideFrame.html 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. <br />
 
</p>
 
</p>
 +
<h3>Getting started with RNA-seq and GSEA</h3>
 +
The GSEA method was originally developed for analysis of microarray data. In order to best adapt this method for RNA-sequencing data sets the GSEA team has developed a [[Using_RNA-seq_Datasets_with_GSEA|collection of guidelines and suggestions which describe how to properly handle these data.]]
 
<h2>MSigDB gene sets</h2>
 
<h2>MSigDB gene sets</h2>
<p> Current release of the Molecular Signatures Database ([[MSigDB_v7.0_Release_Notes|v7.0 MSigDB]]) contains 22,596 gene sets for use with GSEA. For information about MSigDB and the gene sets, see the [http://www.broadinstitute.org/gsea/msigdb MSigDB web site].  </p>
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<p> Current release of the Molecular Signatures Database is divided into two parts, the MSigDB Human Collections, and the MSigDB Mouse collections. Release notes for the current version of the Human collections are available here: ([[MSigDB_v2023.1.Hs_Release_Notes|MSigDB v2023.1.Hs]]) and the release notes for the current version of the Mouse collections are available here: ([[MSigDB_v2023.1.Mm_Release_Notes|MSigDB v2023.1.Mm]]). For information about MSigDB and the gene sets, see the [http://www.broadinstitute.org/gsea/msigdb MSigDB web site].  </p>
<p> Please note that gene sets can change 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. </p>
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<p> Please note that gene sets can change or become deprecated in subsequent releases of MSigDB. It is thus important to indicate the version of MSigDB to fully reference gene sets used in your study. </p>
  
 
<h2>Software</h2>
 
<h2>Software</h2>
 
<p>We provide the following software implementations of the GSEA method:
 
<p>We provide the following software implementations of the GSEA method:
 
<ul>
 
<ul>
     <li>Java desktop application -- Easy-to-use graphical interface that can be run from the [http://www.broadinstitute.org/gsea/downloads.jsp Downloads] page. The [http://www.broadinstitute.org/gsea/doc/GSEAUserGuideFrame.html User Guide] fully describes this application (referred to as GSEA or GSEA-P).
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     <li>Java desktop application -- Easy-to-use graphical interface that can be run from the [http://www.broadinstitute.org/gsea/downloads.jsp Downloads] page. The [http://www.broadinstitute.org/gsea/doc/GSEAUserGuideFrame.html User Guide] fully describes this application in detail.
 
     </li>
 
     </li>
 
     <li>Java jar file -- Command line interface that can be downloaded from the [http://www.broadinstitute.org/gsea/downloads.jsp Downloads] page. See [http://software.broadinstitute.org/gsea/doc/GSEAUserGuideTEXT.htm#_Running_GSEA_from Running GSEA from the Command Line] in the <i>User Guide</i> for details. This might be useful for analyzing several datasets sequentially, analyzing large datasets, or running analyses on a compute cluster.</li>
 
     <li>Java jar file -- Command line interface that can be downloaded from the [http://www.broadinstitute.org/gsea/downloads.jsp Downloads] page. See [http://software.broadinstitute.org/gsea/doc/GSEAUserGuideTEXT.htm#_Running_GSEA_from Running GSEA from the Command Line] in the <i>User Guide</i> for details. This might be useful for analyzing several datasets sequentially, analyzing large datasets, or running analyses on a compute cluster.</li>
     <li>R-GSEA -- R implementation of GSEA that can be downloaded from the [http://www.broadinstitute.org/gsea/downloads_archive.jsp Archived Downloads] page. This implementation is intended for experienced computational biologists who want to tweak and play with algorithm. The [[R-GSEA_Readme|R-GSEA Readme]] provides brief instructions and support is limited. Please note that this implementation has not been actively maintained since 2005.</li>
+
     <li>R-GSEA -- R implementation of GSEA that can be downloaded from the [http://www.broadinstitute.org/gsea/downloads_archive.jsp Archived Downloads] page. This implementation is intended for experienced computational biologists who may want to explore the underlying algorithm. The [[R-GSEA_Readme|R-GSEA Readme]] provides brief instructions and support is limited. Please note that this implementation is not actively maintained or supported.</li>
 
</ul>
 
</ul>
 
</p>
 
</p>
 
<p>Thank you for your interest in GSEA,<br>
 
<p>Thank you for your interest in GSEA,<br>
 
The GSEA Team</p>
 
The GSEA Team</p>

Latest revision as of 19:18, 3 March 2023

GSEA Home | Downloads | Molecular Signatures Database | Documentation | Contact

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 at groups.google.com/group/gsea-help.

    When contacting our team with questions about java GSEA programs, please send the following information:
  • your computer's operation system
  • version of java which you used to run GSEA
  • detailed log transcript from the GSEA session in question

    to view the log, click [+] at the bottom of main screen of GSEA java desktop application, copy the text to a separate file and attach it to your request

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.

Getting started with RNA-seq and GSEA

The GSEA method was originally developed for analysis of microarray data. In order to best adapt this method for RNA-sequencing data sets the GSEA team has developed a collection of guidelines and suggestions which describe how to properly handle these data.

MSigDB gene sets

Current release of the Molecular Signatures Database is divided into two parts, the MSigDB Human Collections, and the MSigDB Mouse collections. Release notes for the current version of the Human collections are available here: (MSigDB v2023.1.Hs) and the release notes for the current version of the Mouse collections are available here: (MSigDB v2023.1.Mm). For information about MSigDB and the gene sets, see the MSigDB web site.

Please note that gene sets can change or become deprecated in subsequent releases of MSigDB. It is thus important to indicate the 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 in detail.
  • Java jar file -- Command line interface that can be downloaded from the Downloads page. See 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 Archived Downloads page. This implementation is intended for experienced computational biologists who may want to explore the underlying algorithm. The R-GSEA Readme provides brief instructions and support is limited. Please note that this implementation is not actively maintained or supported.

Thank you for your interest in GSEA,
The GSEA Team