GenePattern is a powerful genomic analysis platform that provides access to more than 100 tools for gene expression analysis, proteomics, SNP analysis and common data processing tasks. A web-based interface provides easy access to these tools and allows the creation of multi-step analysis pipelines that enable reproducible in silico research.


Getting Started

quickstartLearn to use GenePattern in 10 minutes:
Learn hands-on with the Quick Start tutorial
Learn by watching short video tutorials
onlineRun analyses now at Broad server
Use GenePattern to run analyses on a server at the Broad Institute.
download Download GenePattern
GenePattern runs on Windows, Mac, and Linux.
Citing GenePattern
Reich M, Liefeld T, Gould J, Lerner J, Tamayo P, Mesirov JP GenePattern 2.0 Nature Genetics 38 no. 5 (2006): pp500-501
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What's New

11/9/2009: GenePattern 3.2.1 is now available. Run analyses on the Broad server or download GenePattern. This release includes support for Java 6. For more information, see the release notes.

10/15/2009: Two GenePattern video tutorials are now available.

9/18/2009: Cancer Outlier Profile Analysis (COPA) is now available on the GenePattern public server. An adaptation of the Bioconductor package (copa) by MacDonald (2006), the analysis can be used to identify recurrent chromosomal translocations in microarray data.

6/22/2009: GenePattern 3.2 is now available. New features include the ability to share analysis result files and new pages for tracking and reviewing analysis jobs. For more information, see the release notes.

5/29/2009: The FLAME modules are now available on the GenePattern public server. They can be used to define and characterize discrete populations in flow cytometric data using FLow analysis with Automated Multivariate Estimation as published by Pyne, et al. in PNAS (2009) 106:8519-8524.

3/10/2009: The ESPPredictor module is now available on the GenePattern public server. It provides a means of predicting, from sequence alone, which peptides for any given protein are likely to work well for targeted mass spec assay development, as described by Fusaro, V., et al. in Nature Biotechnology (2009) 27:190-198.



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best practices award Winner of the Editor's Choice award for the 2005 BioIT World Best Practices competition.