Case Study: CardioDx achieves faster genomic diagnostics analysis with Revolution Analytics

Complex Data Sets in Genomic Diagnostics Require Multiple Analytic Methods

CardioDx, a cardiovascular genomic diagnostics company, faced a major challenge analyzing complex clinical data from thousands of patients to build diagnostic algorithms for assessing obstructive coronary artery disease. The team relied heavily on R for its biostatistical work, and turned to Revolution Analytics’ Revolution R products to help speed up highly iterative analyses of large, variable-rich data sets.

Revolution Analytics implemented faster analytic tools that worked alongside open-source R packages, allowing CardioDx to run large-scale analyses more efficiently without sacrificing accuracy. The result was improved processing speed, reduced overall project time, and greater team efficiency; CardioDx reported that Revolution R was faster than regular R and helped them build diagnostic algorithms more quickly.

CardioDx