Wellcome Trust continues funds for Edinburgh's SPRINT
high-performance gene-analysis tool
7 August 2009
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, the Edinburgh Parallel Computing
Centre (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.”
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