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SIGNATURE: a workbench for gene expression signature analysis
Jeffrey T Chang1, Michael L Gatza, Joseph E Lucas
1Department of Integrative Biology and Pharmacology, University of Texas Health Science Center at Houston, Houston, TX, USA. jeffrey.t.chang@uth.tmc.edu
BMC Bioinformatics
|November 15, 2011
Summary
SIGNATURE is a new web-based tool simplifying gene expression signature analysis. It uses Bayesian methods and a curated database within an accessible GenePattern interface, reducing the technical burden for researchers.
Area of Science:
- Genomics
- Bioinformatics
- Computational Biology
Background:
- Cellular phenotypes are determined by gene expression.
- Measuring gene expression allows for precise phenotype definition.
- Current gene expression analysis tools are complex and require specialized expertise.
Purpose of the Study:
- To develop an intelligent software tool that simplifies gene expression signature analysis.
- To reduce the technical burden associated with gene expression data analysis.
Main Methods:
- Development of SIGNATURE, a web-based resource.
- Utilizing Bayesian methods for gene expression data processing.
- Integration with a curated database of gene expression signatures.
- Implementation within the GenePattern web interface.
Main Results:
- SIGNATURE simplifies gene expression signature analysis.
- The resource provides software, data, and protocols for successful analysis.
- Bayesian methods and a curated database are integrated for ease of use.
Conclusions:
- SIGNATURE is publicly available at http://genepattern.genome.duke.edu/signature/.
- The tool aims to make gene expression analysis more accessible to researchers.
