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
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