This project will set up a unique cloud computing facility which will enable research on the world’s largest and most comprehensive cancer genome dataset. Using the facilities of the Cancer Genome Collaboratory, researchers will be able run complex data mining and analysis operations across 10 to 15 petabytes of cancer genome sequences and their associated donor clinical information.
Using advanced metadata tagging, provenance tracking, and workflow management software, researchers will be able to execute complex analytic pipelines, create reproducible traces of each computational step, and share methods and results. This represents a fundamental reversal in the current practice of genome analysis. Rather than requiring researchers to spend weeks downloading hundreds of terabytes of data from a central repository before computations can begin, researchers will upload their analytic software into the Collaboratory cloud, run it, and download the compiled results in a secure fashion.
Since the genetic data used in the Collaboratory is so detailed as to permit personal identification, privacy issues are central to the project’s design. A special team of computer scientists will investigate ways to guard the privacy of everyone whose data are analyzed. These will include techniques to make genetic profiles anonymous without the loss of details that would render the profiles overly vague, and techniques to structure queries from health researchers so they can be processed via secure data storage sites.