Wouldn't it be reasonable to use the sigma one calculates from the
sigmaA? That sigma would reflect the uncertainty in the calculated
structure factor amplitude due to the uncertainty in the parameters
in your model. Of course, one then realizes that you should down
weight you structure factors amplitudes with sigmaA too. Then you
would have a set of structure factors amplitudes and sigmas that
reflects the uncertainties of your model.
If you don't believe in the idea of sigmaA's "cloud" of possible
atoms and just want the structure factors of your PDB file, as though
you know all the parameters to infinite precision, your sigma would
only be non-zero because of uncertainties due to numerical problems
in the Fourier Transform. These sigmas would be very small, in most
cases, and be determined by the method you used to perform the
calculation. This is probably not a useful solution.
Dale Tronrud
Peter Adrian Meyer wrote:
I add a fake "sigma" column for each "data" column because so many
programs require one.
This is slightly tangential, but does anyone know of a good way to
generate semi-realistic sigma values for calculated/simulated data?
The best I've been able to do is borrow from an experimental dataset of
the same protein (after scaling), but that doesn't work unless you've got
an experimental dataset corresponding to your simulated one. I also tried
a least-squares fit (following a reference I don't have in front of
me...this was a while ago), which didn't result in a good fit for our
data.
Pete
Pete Meyer
Fu Lab
BMCB grad student
Cornell University
