I've just started seriously looking at Galaxy, and I already have a suggestion (everyone's a critic...): switch from using rpy or even rpy2 to scipy/numpy/matplotlib for basic statistics and plots. I wrestled a bit with getting rpy to work on my local setup and decided it would be quicker to write my own plotting tool extensions, which indeed turned out to be the case. Since you already require python it seems much more natural to use python-native tools.
To give some positive feedback, learning to write an extension was surprisingly easy and encourages me to work on more.
I use currently use Sage (http://www.sagemath.org/) to both analyze next-generation sequence data (454 and Illumina) and create interactive tools for the biologists I collaborate with. The Sage project involves many of the same issues and challenges facing Galaxy. Sage is based on python, but includes R. I realize that there are many things you would want to do with R that aren't included in scipy/biopython, so it might be worthwhile to look at how Sage wraps R. Its far from perfect, but I prefer it to rpy2. In the Sage source tree the interface is at: $SAGE_ROOT/devel/sage/sage/interfaces/r.py. (Ugly online copy at: http://hg.sagemath.org/sage-main/file/361a4ad7d52c/sage/interfaces/r.py).
-Marshall Hampton Department of Mathematics and Statistics and the Integrated Biosciences Program University of Minnesota Duluth