Gene analysis is becoming increasingly complex and can be greatly enhanced by exploiting the power of high-performance computing (HPC), but the software can be difficult for researchers to use. To allow greater access to the benefits of HPC, EPCC and the Division of Pathway Medicine at the University of Edinburgh developed a prototype framework called SPRINT, which allows biostatisticians to more easily exploit HPC systems. The Wellcome Trust has now funded the SPRINT project for a further two years. This will allow the development of the SPRINT framework and for a number of commonly used functions to be added to enable its use by a wide community.
SPRINT (Simple Parallel R INTerface) is an easy-to-use parallel version of R, a statistical language that processes the data gleaned from microarray analysis, a technique which allows the simultaneous measurement of thousands to millions of genes or sequences across tens to thousands of different samples.
Processing the data that is produced by microarray analysis tests the limits of existing bioinformatics computing infrastructure. A solution is to use HPC systems, which offer more processors and memory than desktop computer systems.
However, R must be able to utilise multiple processors if it is to fully exploit the power of HPC systems to analyse genomic data. There are existing modules that enable R to do this, but they are either difficult for HPC novices or cannot be used to solve certain classes of problem. SPRINT allows parallelised functions to be added to R without the need to master parallel programming methods, enabling the easy exploitation of HPC systems.
Prof. Peter Ghazal, director of the Division of Pathway Medicine, says "SPRINT will greatly increase the computing power available to many researchers and is therefore a unique opportunity to accelerate the discovery of the genes linked to diseases."
- SPRINT requires very little modification to existing sequential R scripts. As an example the project team created a function that carries out the computation of a pairwise calculated correlation matrix. This performs well with SPRINT. When executed using SPRINT on an HPC resource of eight processors this computation reduces by more than three times the time R takes to complete it on one processor.
- SPRINT is open-source and external contributions and collaborations are encouraged
- A two year project started on 1st April 2009 to develop the framework and add a number of commonly used functions to SPRINT to enable its use by a wide community. This work is supported by the Wellcome Trust Technology Development Grant [086696/Z/08/Z].
For further information, please visit:
http://www.r-sprint.org
About EPCC
EPCC is a leading European centre of expertise in advanced research, technology transfer and the provision of supercomputer services to academia and business. For more information, please visit www.epcc.ed.ac.uk.
Division of Pathway Medicine
The central goal of the Division of Pathway Medicine, a research centre in the College of Medicine and Veterinary Medicine at the University of Edinburgh, is to integrate post-genomic science with medicine in order to provide a better mechanism-based understanding of disease processes. This will provide the basis for the development of new medical innovations for the diagnosis and treatment of human diseases, which the Division is committed to extending to the developing world. For more information, please visit www.pathwaymedicine.ed.ac.uk