Melody Lin wrote:
Hi all,
I have always been wondering... for a data set diffracting to say 2.15
Angstrom but in the highest resolution shell (2.25-2.15) the
completeness is 74%, should I use merge all the data and call it a 2.15
A dataset or I should cut the data set to say 2.25 A where the highest
resolution shell has better completeness (>85%)? What is an acceptable
completeness value for the highest resolution shell?
Thank you.
Best,
Melody
Hi Melody,
This reply is not aimed at you directly as this situation seems to have
become systemic in the field. So thanks for bringing it up!
We can have a long, and mostly aimless, discussion on what resolution
you should claim for your data set but DON'T throw away good data to
make the statistics look better. At high resolution the statistics are
supposed to get worse! What matters is if the data still contain useful
information. The fact that 26% of the data is missing does not normally
mean that anything is wrong with the 74% that you did measure. Perhaps
you used a square detector and didn't place it close enough to capture
the full resolution, or perhaps your diffraction pattern is anisotropic.
The only reason to throw out data is if they are too inaccurate for your
purpose. When your data is used for phasing, especially anomalous
phasing, there is reason to focus on data quality, but I see far too
many native data sets that make poor use of the diffraction potential of
the crystal. I thought this was due to people not properly collecting
the data, but now it seems that people are simply throwing away good
data because they don't like the statistics.
So my advice; if your high resolution shell data has poor completeness
then check why this happened. If you did not collect the data properly
then let it be a lesson for the next data collection trip. If it
resulted from some issue of the crystal then decide if the measured data
is messed up as well. If not then use all the data you trust, which
means there is useful signal (I/SigI >1.5 or >2.0 depending who you talk
to) and no problems leading to systematic errors or outliers.
Bart
==============================================================================
Bart Hazes (Assistant Professor)
Dept. of Medical Microbiology & Immunology
University of Alberta
1-15 Medical Sciences Building
Edmonton, Alberta
Canada, T6G 2H7
phone: 1-780-492-0042
fax: 1-780-492-7521
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