Ah, yes, I was missing that. The statistics will be wrong. But in principle I will get an mtz with better data, because I am integrating more observations which would have been rejected by being missed at low resolution if the mosaicity was set too low or being rejected by overlaps at high resolution if the mosaicity is increased.
So the question is - can I use this data for refinement? Or should I stick with the best of the datasets (the one with the highest completeness and multiplicity)?
Thanks!
Jose
On Jan 28, 2011, at 28/1/11 - 11:59, Ian Tickle wrote:
Jose - you're missing the fact that the same dataset processed in
different ways are not statistically independent datasets! Increasing
the multiplicity for independent data reduces the uncertainty because
the calculation of the SU assumes statistical independence.
Cheers
-- Ian
On Fri, Jan 28, 2011 at 11:46 AM, José Trincão <[log in to unmask]> wrote:
> Hello all,
> I have been trying to squeeze the most out of a bad data set (P1, anisotropic, crystals not reproducible). I had very incomplete data due to high mosaicity and lots of overlaps. The completeness was about 80% overall to ~3A. Yesterday I noticed that I could process the data much better fixing the mosaicity to 0.5 in imosflm. I got about 95% complete up to 2.5A but with a multiplicity of 1.7. I tried to integrate the same data fixing the mosaicity at different values ranging from 0.2 to 0.6 and saw the trend in completeness, Rmerge and multiplicity.
> Now, is there any reason why I should not just merge all these together and feed them to scala in order to increase multiplicity?
> Am I missing something?
>
> Thanks for any comments!
>
> Jose
>
>
> José Trincão, PhD CQFB@FCT-UNL
> 2829-516 Caparica, Portugal
>
> "It's very hard to make predictions... especially about the future" - Niels Bohr
>
José Trincão, PhD CQFB@FCT-UNL
2829-516 Caparica, Portugal
"It's very hard to make predictions... especially about the future" - Niels Bohr
José Trincão, PhD CQFB@FCT-UNL
2829-516 Caparica, Portugal
"It's very hard to make predictions... especially about the future" - Niels Bohr
|