Methods of collapsing rare/common variants for mapping the assocition to traits in next generation sequencing

The time of next generation sequencing (NGS) comes so quick, and all of the sudden all the meetings and journals are ready to welcome for NGS time. This reflects to our research as well. I submitted a grant with transferring the concept of joint analysis of family and unrelated data to NGS. Then we quickly merged to 3 NGS projects.

Non-enough of explaining the most mapped common alleles to common diseases, people swarmed to rare variants. However, some rare variants will explain the disease, some may not since many of them are maybe only the results of evolution. Besides, due to its rare occurrence, larger sample size is needed to draw statistical conclusions. Yet many of the rare variants may occur as random mutations and be rare to repeat in population. All of these made the association study more difficult.

We reviewed the recent papers about rare variants. But most used the simulated data including Li and Neal,AJHG, 2008, Madsen and Browning, PLOS genetics, 2009 and Price et al. AJHG, 2009. The basic idea is that people are trying to upweight the rare variants that have true associations. It also seems that a bunch of GAW17 people are working on the same or similar topic. Obviously, it is worth to dig something here. But I have some little concerns whether it's worthy to draw so much attention?