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Scaling algorithms in data reduction programs are based on parameterising
the experiment independent of the symmetry of the data, though they of
course use symmetry related data to determine the scales.

Actually this is a perfect case for scaling, because you have lots of
information to determine the parameters.

This sort of anisotropy will probably come out in a apparent absorption
correction, usually expressed as spherical harmonic terms on the
diffracted beam direction (eg in Scala)

Phil

>
>
> My favorite protein crystallizes in P4332 (cubic).  In a cubic spacegroup,
> it appears that all data processing programs (please correct me if I am
> wrong) expect ones data to drop off perfectly isotropically with respect
> to resolution.  Obviously with a perfect cubic crystal this should be the
> case.  However, when crystals are not uniform in shape, or when they are
> stressed during handling I frequently encounter crystals which show
> anisotropy in their diffraction patterns and which are consequently
> difficult to index/scale in the cubic spacegroup.  Scaling things in
> (e.g.) P212121 or P43212 lowers the redundancy and thus the effective
> resolution with only a modest improvement in R factors.  It
> really seems like I am sacrificing information content in order
> to allow the scaling algorithm to cope with the data anisotropy.
> Collecting full P212121 datasets is also unappealing because the crystals
> are sensitive to radiation (probably due to sample heating and damage
> near lattice contacts ;).  What it seems I really need is a way to
> anisotropically scale the data Bs along h,k, and l, to correct for the
> differences in the quality of diffraction in different directions, but
> then I would like to be able to take the thusly scaled intensities and
> combine them to produce a P4332 dataset.
>
> Any thoughts?
>
>
> _____________________________________________
> -  Joshua Warren, PhD ([EMAIL PROTECTED])   -
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