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Scientists at the Ó³»­´«Ã½ of MIT and Harvard recently released GenePattern 2.0, an enhanced version of the integrative software tool for analyzing gene expression data. As described in the May issue of Nature Genetics, GenePattern provides a variety of analytic and visualization functions that enable researchers to perform custom data analyses and to record them for later playback. The updated software includes several new components that permit the analysis of proteomic data and improve its ability to capture and recall the individual steps in the analytic process. GenePattern is freely available to the research community and provides multiple user interfaces, which accommodate the needs of researchers with programming experience as well as those without it.

"The strengths that GenePattern brings to gene expression analysis can now be similarly realized for proteomic data," said Michael Reich, lead author of the Nature Genetics letter, manager of cancer informatics development at the Ó³»­´«Ã½, and the group leader for GenePattern. "We have also added features to improve its ability to capture and reproduce analyses, which is vital to researchers both individually and as a community."

The new additions to GenePattern enable researchers to process proteomic data and include modules for data processing, analysis, and visualization. Other enhancements supplement its reproducibility features, which include automatically recording the individual steps in an analytic process so they can be repeated or shared with other researchers, and storing both the data and all versions of the methodologies used to manipulate them. These aspects of GenePattern are key facilitators for replicating in silico research findings by independent researchers.

"GenePattern meets the ever-changing needs of researchers in the age of genomic science," said Jill Mesirov, senior author of the Nature Genetics letter, chief informatics officer, and director of Computational Biology and Bioinformatics at the Ó³»­´«Ã½. "These new capabilities are a vivid illustration of the tool's flexibility and adaptability, as well as our commitment to the goal of reproducible research."

In the future, scientists plan to incorporate additional improvements to the GenePattern software. These include capabilities for analyzing single nucleotide polymorphism (SNP) data, such as copy number estimation, loss of heterozygosity determination, and the identification of chromosomal amplifications and deletions. This information forms the core components for discovering the genomic alterations that contribute to cancer and other human diseases.

Currently, there are over 2,300 registered GenePattern users worldwide, including more than 500 institutions and 30 pharma-biotech companies. In 2005, GenePattern received the Editor's Choice award in the Bio-IT World Best Practices competition.

The updated software and a comprehensive list of new features and fixes can be found on the website.

GenePattern is supported by funding from the National Institutes of Health.

Reich M¹, Liefeld T¹, Gould J¹, Tamayo P¹, Mesirov JP¹. Nature Genetics; doi:10.1038/ng1785

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