One of the major
difficulties for many laboratories setting up proteomics programs has been obtaining an
d maintaining the computational infrastructure require
d for the analysis of the large flow of proteomics
data. We
describe a system that combines
distribute
d clou
d computing an
d open source software to allow laboratories to set up scalable virtual proteomics analysis clusters without the investment in computational har
dware or software licensing fees. A
dditionally, the pricing structure of
distribute
d computing provi
ders, such as Amazon Web Services, allows laboratories or even in
divi
duals to have large-scale computational resources at their
disposal at a very low cost per run. We provi
de
detaile
d step-by-step instructions on how to implement the virtual proteomics analysis clusters as well as a list of current available preconfigure
d Amazon machine images containing the OMSSA an
d X!Tan
dem search algorithms an
d sequence
databases on the Me
dical College of Wisconsin Proteomics Center Web site (
du/vipdac" class="extLink">http://proteomics.mcw.edu/vipdac).