Increasing redundancy only helps if all data draw from the same
distribution so you get a more accurate estimate of the mean of the
distribution. When dealing with different crystals, crystal-to-crystal
variation is likely larger than the anomalous signal you are looking for
and I'm therefore not convinced that merging of data is a good idea
(never hurts to try though).
I wonder if it would work better to derive anomalous differences for the
individual data sets first and then merge those anomalous differences.
This may allow the subtraction between F+ and F- to remove some of the
systematic differences there may be between crystal forms.
Bart
Kay Diederichs wrote:
> hari jayaram schrieb:
> ...
>
>> I was wondering if anyone could comment on combining datasets from
>> multiple P1 crystals to increase the redundancy even further for such
>> heavy atom ( SAS / SAD ) or MAD experiments.
>>
>
> Hari,
>
> well, my comment would be that it should be possible in principle from
> what you describe, but the outcome strongly depends on the details (size
> of expected and observed anomalous and isomorphous signal, internal
> anomalous correlation coefficients, I/sigma and R-factors, radiation
> damage, are crystals isomorphous, ...).
>
> To increase the quality of the reduced data it would be advisable to
> rotate around different axes, which is possible at some - but not all -
> beamlines. This is even more true in P1.
>
> For all of the major data reduction programs there exist specific
> programs for merging data, and it does make a lot of sense to merge your
> passes (but don't merge radiation-damaged data with undamaged data)!. I
> would suggest to use at least two different data reduction packages -
> everything depends on the quality of the data reduction, and the
> programs have strengths in different areas.
>
> HTH,
>
> Kay
--
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Bart Hazes (Assistant Professor)
Dept. of Medical Microbiology & Immunology
University of Alberta
1-15 Medical Sciences Building
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Canada, T6G 2H7
phone: 1-780-492-0042
fax: 1-780-492-7521
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