The flood of genomic data is revolutionizing our approach to understanding normal cellular processes and the mechanisms of disease. This has driven the development of sophisticated computational methods to enable the analysis of this data, and a new emphasis on integrative techniques. It is critical to empower scientists with domain expertise by giving them direct access to these new technologies and techniques for analysis and interpretation. However, complex computational methods can be difficult to understand and use correctly. They may not easily work together or be reproduced. Since 2004 we have been sharing advanced mathematical methods and computational algorithms for genomic analysis with the research community in a user-friendly, freely available software package, GenePattern. The power of GenePattern is its accessibility to a broad community of users, the ability to access and interoperate a library of analytic and visualization modules, the ease with which the environment supports the rapid development and dissemination of new methods, and the reproducibility of computational research. Our goal for this renewal is to evolve and enhance the GenePattern platform to support the changing face of modern biomedical research brought on by new data acquisition platforms, new methods, and new genomics projects. We propose to broaden the content of the module repository to meet these new scientific challenges, and to serve the community's projects by providing a robust, scalable data processing platform. In addition, we will continue to provide and enhance our user support, training, and documentation.
Aim 1. Expanding GenePattern's module repository and providing interoperability with our Integrative Genomics Viewer to better support users and their research.
Aim 2. Extending GenePattern for general production and next-generation sequencing data processing for use by a wide range of genomics projects.
Aim 3. Training, documentation, continuing maintenance and support for the GenePattern package. Our progress over our previous funding period, extensive experience in software engineering, significant user base, large repository of genomic analysis tools, documentation and training for users make us well poised to carry out the aims of this proposal.

Public Health Relevance

The GenePattern genomic analysis environment puts sophisticated computational methods within the reach of all biomedical researchers. Through the analysis of the increasing amount of available genomic data, GenePattern is used to address a variety of problems at the forefront of biomedical research including patient diagnosis and prognosis, identification of new drug targets, and understanding biological mechanisms. The work in this project will improve the GenePattern software by expanding the tools and methods it contains and enhance its capabilities to make it even better able to support the broadest range of biomedical researchers and large genomics projects tackling the important questions facing them today.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM074024-09
Application #
8601186
Study Section
Special Emphasis Panel (ZRG1-BST-H (50))
Program Officer
Brazhnik, Paul
Project Start
2005-06-01
Project End
2014-12-31
Budget Start
2014-01-01
Budget End
2014-12-31
Support Year
9
Fiscal Year
2014
Total Cost
$520,795
Indirect Cost
$206,778
Name
Broad Institute, Inc.
Department
Type
DUNS #
623544785
City
Cambridge
State
MA
Country
United States
Zip Code
02142
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Robinson, James T; Thorvaldsdottir, Helga; Winckler, Wendy et al. (2011) Integrative genomics viewer. Nat Biotechnol 29:24-6
Tamayo, Pablo; Cho, Yoon-Jae; Tsherniak, Aviad et al. (2011) Predicting relapse in patients with medulloblastoma by integrating evidence from clinical and genomic features. J Clin Oncol 29:1415-23
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