SPRINT: A Parallel Framework for R

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• Speaker to be confirmed
• Friday 26 April 2013, 14:00-15:00
• 215.

If you have a question about this talk, please contact Nicholas Shannon.

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 tests the limits of existing bioinformatics computing infrastructure. A solution to this issue is to use High Performance Computing (HPC) systems, which contain many processors and more memory than desktop computer systems.

We have designed and built a framework that allows the addition of parallelised functions to R to enable the easy exploitation of HPC systems. The Simple Parallel R IN Terface (SPRINT) is a wrapper around such 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.

This talk is part of the CRI joint computational biology meeting series.

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