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
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