Revolution R Enterprise implemented at CardioDX

Revolution Analytics, the leading provider of commercial software and support for the popular open source R statistics language, today announced the successful implementation of its signature product, Revolution R Enterprise, by biostatisticians at CardioDX, a genomic research firm. Revolution R was used to design the Corus CAD® test, the first test of its kind to analyze genomic data and identify at-risk patients for coronary artery disease (CAD) without requiring an invasive procedure. The Corus CAD® test was recently honored as one of TIME Magazine's "Top Ten Medical Breakthroughs of 2010".

“We've seen strong growth in this sector over the past year. Seeing such wide adoption of Revolution R complement these research endeavors is a testament to its ability to execute complex tasks with even greater speed than open source R.”

Revolution R was used to help develop the algorithm that powers the Corus CAD® test. To do so, biostatisticians at CardioDX analyzed over 10 gigabytes of genomic data to ultimately identify 23 predictive genes for CAD. In addition to using open source R, biostatisticians at CardioDX employ Revolution R in their daily research, citing its unparalleled flexibility and power for analyzing large and complex data sets in R.

"Analyzing clinical data from thousands of patients poses a serious analytical challenge," said Michael Elashoff, Director of Biostatistics at CardioDX. "We rely on R for nearly all of our research projects because it allows us to run accurate and effective analyses. Revolution R offers even greater speed than open source R and allowed us to run analyses for the Corus CAD® faster than we could with any alternative. This was especially beneficial for us considering the fact that it took over one million separate analyses to develop this algorithm."

Revolution R Enterprise continues to be the premier production-grade analytics software built for advanced R statistics computing. The flagship product features higher performance, greater scalability and stronger reliability to R at a fraction of the cost of legacy products.

"R is used heavily by life sciences companies that perform advanced biological research-scientists know R and are comfortable working with it," said Revolution Analytics COO Jeff Erhardt. "We've seen strong growth in this sector over the past year. Seeing such wide adoption of Revolution R complement these research endeavors is a testament to its ability to execute complex tasks with even greater speed than open source R."