SPRINT provides easy access to high-performance computing for the analysis of high-throughput, post-genomic data using the statistical programming language R.

Microarray analysis allows the simultaneous measurement of thousands to millions of genes or sequences across tens to thousands of different samples. The analysis of the resulting data pushes the limits of current, bioinformatics computing infrastructure: a solution is to use High Performance Computing (HPC).

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SPRINT allows the addition of parallelised functions to R, which enables the easy exploitation of HPC systems. The Simple Parallel R INTerface (SPRINT) is a wrapper around these parallelised functions. Their use requires very little modification to existing sequential R scripts and no expertise in parallel computing. SPRINT allows the biostatistician to concentrate on the research problems rather than the computation, while still allowing exploitation of HPC systems. It is easy to use and with further development will become more useful as more functions are added to the framework.

The Software Sustainability Institute are helping SPRINT to improve their user engagement and provide improved resources and support. We are working with SPRINT to develop their user documentation and training materials, and offer a local installation service to the Centre for Cardiovascular Research and Institute of Evolutionary Biology (both at the University of Edinburgh). This will ease access to SPRINT, enabling greater take-up of the software and allowing more researchers to benefit from SPRINT’s capabilities. This will also enhance the prospect of future contributions from users that are key to SPRINT’s longevity.

Our developers are working with teams from SPRINT, the Institute of Evolutionary Biology and the Centre for Cardiovascular Research to add functionality to SPRINT and R to enable the processing of next-generation sequencing data.