*blinks*
Thanks for sharing these screenshots. I've run them by our colleagues, and none of us recall ever seeing an analysis do this before. There are no known bugs that would lead to this behavior internally, and the sections of code that generate the QQ and manhattan plots are reasonably independent (since both show oddities, this suggests it is a real artifact in your data).
Since the behavior appears systematic across the entire genome, my colleague suggests running some QC on the results, such as calculating the genomic control (GC). If it is high, the problem is likely to be in your original data. (similarly, a simple histogram of -log10pvalues in your data could help shed light on whether the manhattan plot behavior reflects your data)
I'd be curious to hear what you find- even if it doesn't indicate a bug, it sounds like a chance to learn something about the odd corners of GWAS, and perhaps to improve the summary info that we provide to users in the future.
-Andy Boughton
abo...@umich.eduSenior Applications Programmer/Analyst
Center for Statistical Genetics
University of Michigan