"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 Ama
|Contact: Eileen La Susa|
Medical College of Wisconsin