Gene expression analysis software

Dec 20 2004

Case Western Reserve University has announced that its BAMarray™ software is now available for download and licensing. The statistical software analyzes gene expression data -- one of the hottest areas of biology research.

Gene expression data is becoming abundant with the popularity of microarrays. Microarrays, or gene chips, allow researchers to simultaneously assess the relative expression of thousands of genes. While this technology produces rich sources of data, the analysis of such data proves troublesome. BAMarray virtually eliminates the time-consuming step of evaluating which genes are affected by an experiment and require further study.

BAMarray analyzes the genomic data extracted from microarrays and produces lists of genes that show biologically interesting expression profiles across experimental groups. The software provides both diagnostic and inferential graphical plots to help users better understand their data. The user can interactively view, zoom in, label, and generate lists of color coded genes that were significantly up-regulated or down-regulated.

Sanford Markowitz, M.D., the Ingall Professor of Cancer Genetics at the Case Western Reserve University School of Medicine and University Hospitals of Cleveland and an investigator with the Howard Hughes Medical Institute, searches for the genes involved in the development of colon cancer and has incorporated BAM into his research. He said, "BAM technology allows us to find genes with important expression changes in colon cancer that we could not have found using other approaches."

BAMarrayTM software incorporates the Bayesian Analysis of Variance for Microarrays (BAM) methodology developed jointly at the Case and Cleveland Clinic Foundation Departments of Biostatistics and Epidemiology by J. Sunil Rao of Case and Hemant Ishwaran of the Cleveland Clinic Foundation. The methodology relies on a special type of inferential regularization that allows it to find more truly differentially expressing genes.

"The technique allows researchers to discover statistically significant genes from gene chip experiments that are normally hidden in statistical noise," said Ishwaran.

"Researchers here at Case have already found our methodology useful," said Rao. "We are thrilled that this software is now available to scientists everywhere."

"We've positioned this software for quick distribution and ease of use," said Ian Spatz, the case manager in the Case Technology Transfer Office responsible for the project. "I fully expect significant discoveries to be made using this powerful tool."

Joe Jankowski, assistant vice-president for biomedical sciences, added "This software is a great example of in-house technology validation. With Case's support, Rao and Ishwaran have been able to make a complex analysis technique simple and easy to use."