Dear All,
I have two questions:
1) I have collected multiple, native datasets (5) from the same
crystal (different parts of the crystals exposed with different
transmission and oscillation angles). Each dataset on its own is close
to complete (96-98 %). Naturally, differences in exposure, onset of
radiation damage (datasets were collected with high transmission),
local differences in the crystal, will affect the variance of the
errors in the measurements for the reflections between the different
datasets; but I would think the redundancy and increased number of
measurements from all datasets should outweigh this. My tendency is to
include all datasets.
I am working at 3.8 A resolution (structure is solved; 80 % solvent
content). Missing even a few reflection will probably have more of an
impact at this lower than at higher resolution. Essentially, I am
trying to obtain better signal in the resolution range 4-3.8 A, where
there is also diffuse scattering from the solvent between 4 and 3 A
and ice rings and the signal from the individual datasets is weak.
Obviously the criterion will be the calculated map quality, but wanted
to know what some experiences of people have been in such cases.
Should I merge the datasets or rather use them individually for map
calculations?
2) What's the quickest/easiest way to ensure equivalent indexing in
ccp4/imosflm/scala, when merging different datasets together (space
group P6222) (in XDS there is reference_data_set). Use pointless then
cad+scala?
Cheers,
Florian
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