As nth generation DNA sequencing technology moves out of the research lab and closer to the diagnostician's desktop, the process bottleneck will quickly become information processing. The Defense Threat Reduction Agency (DTRA) and the Department of Defense are interested in averting this logjam by fostering the development of new diagnostic algorithms capable of processing sequence data rapidly in a realistic, moderate-to-low resource setting. With this goal in mind, DTRA is sponsoring an algorithm development challenge.
Given raw sequence read data from a complex diagnostic sample, what algorithm can most rapidly and accurately characterize the sample, with the least computational overhead?
My instinct is to keep this to myself because, well, I want to win. But my sharing side of things won out and I am posting here. Maybe we (i..e, the community) can develop an open, collaborative project to do this? Just a thought ...