Researchers at the Medical College
of Wisconsin Biotechnology and Bioengineering Center in Milwaukee have just
made the very expensive and promising area of protein research more accessible
to scientists worldwide.
They have developed a set of free tools called ViPDAC (virtual proteomics data
analysis cluster), to be used in combination with Amazon's inexpensive "cloud
computing" service, which provides the option to rent processing time on
its powerful servers; and free open-source software from the National Institutes
of Health (NIH) and the University of Manitoba.
Their research appears online in Journal of Proteomic Research and is funded
by the NIH Heart Lung and Blood Institute's Proteomics Innovation Center at
the Medical College. Proteomics is a biomedical research term used to describe
the large-scale study of all the proteins expressed by an organism. It usually
involves the identification of proteins and determination of their modifications
in both normal and disease states.
One of the major challenges for many laboratories setting up proteomics programs
has been obtaining and maintaining the very costly computational infrastructure
required for analysis of the vast flow of proteomics data generated by mass
spectrometry instruments used to determine the elemental composition as well
as chemical structure of a molecule, according to senior investigator, Simon
Twigger, Ph.D., assistant professor of physiology.
"We're applying this technology in our Proteomics Center to study cardiovascular
disease, the effects of radiation damage, and in our collaboration with the
University of Wisconsin- Madison stem cell research group," he says.
With cloud computing making the analysis less expensive and more accessible,
many more users can set up and customize their own systems. Investigators can
analyze their data in greater depth than previously possible, making it possible
for them to learn more about the systems they are studying.
"The tools we have produced allow anyone with a credit card, anywhere
in the world, to analyze proteomics data in the cloud and reap the benefits
of having significant computing resources to speed up their data analysis,"
says lead author Brian Halligan, Ph.D., research scientist in the Biotechnology
and Bioengineering Center.
"For researchers currently without access to large computer resources,
this greatly increases the options to analyze their data. They can now undertake
more complex analyses or try different approaches that were simply not feasible
for them before."
Until recently, the standard software programs used for proteomics data analysis
were almost exclusively commercial, proprietary and expensive. Fees for commercial
applications typically rivaled or exceeded the cost of the hardware to run them.
In 2004, a group from the NIH developed and distributed an open-source alternative
to commercial proteomics search programs, entitled Open Mass Spectrometry Algorithm
(OMSSA). A second open-source proteomics database search is also now available;
the X!Tandem, developed and released by the Bevis Laboratory at the University
of Manitoba.
A link on the College's Proteomics Center website http://proteomics.mcw.edu/vipdac
provides detailed step-by-step instructions on how to implement the virtual
proteomics analysis clusters, as well as a list of current available preconfigured
Amazon machine images containing the OMSSA and X!Tandem search algorithms and
sequence databases.
"We describe a system that combines distributed-on-demand cloud computing
and open source software to allow laboratories to set up scalable virtual proteomics
analysis clusters without a huge investment in computational hardware or software
licensing fees," says Dr. Halligan.
"The pricing structure of distributed computing providers such as Amazon
Web Services allows laboratories, or even individuals, to have large-scale computational
resources at their disposal at very low cost per run."
Posted April 10th, 2009
