Dear Clemens, Claus, Ian and Gerard,
since you ask for crowd sourcing, I'll give you my thoughts.
I think the term "anisotropy" is used in many ways to describe very
different events. It actually means the opposite of isotropy, so it is
coviniently used to describe a difference in resolution limits, or
atomic displacement parameters, or ... a difference in wilson distribution.
In my experience, I distinguish these phenomenon.
But first, I've always addressed your point on resolution limit by
splitting my data in 2 sets (cut and uncut), and submitting each set to
BUSTER, Refmac and Phenix.refine and judge the electron-density map
output. And well, the results are similar in some zones, and different
in others. Sometimes it is the 2fofc, sometimes the difference map.
Since I've always coupled "anisotropy" and "difference in resolution
limits" to low resolution membrane proteins, the interpretation of
electron density maps could be challenging. So I used maps coming from
all 3 software to make the best guess.
And each software deals with these information in each own way, so it's
not necessary beneficial to feed corrected data to another software than
buster.
This procedure is easily testable to produce data, judging the "best
result" is very linked to interpretation by eye however.
About the data itself, my guess is that 2 phenomena co-exist.
1/ A lack of order in the crystal in certain direction of real space,
leading to absence (or weak) diffraction in reciprocal space. (my
analysis suggests that it is different than crystal contact, I'm really
thinking of order of diffracting elements).
2/ A different wilson distribution on intensities in 3D. As we have
exchanged, I've identified a peak in intensity profile for membrane
proteins and it would be interesting to investigate how the peak
distributes in 3D reciprocal space as a function of protein packing in
real space. I believe you have all the tools at hand to investigate this
via PDBpeep. If I were to investigate this, I would look at 2 tabs,
looking at wilson distribution on the left by say 10° slices (?), and
one the right the crystal packing seen from the X-ray beam. From that, I
would then look at theoretical diffraction, and departure from that.
If you are looking for chanllenging data, I have a few to share. (to
anyone interested).
All the best
Vincent
Le 04/10/2022 à 18:01, Gerard Bricogne a écrit :
Dear all,
First of all, apologies for breaking the threads entitled "PAIREF -
Warning - not enough free reflections in resolution bin" and "Anisotropy" by
merging them into a new one, but it somehow felt rather against nature to
keep them separate.
Since the early days of the availability of STARANISO [1] (the actual
starting year for the Web server [2] was 2016), we had a hunch that much of
what was happening in the PAIREF procedure might simply be the detection of
the existence of significant data beyond an initially chosen resolution
cut-off not only as a result of an excessively conservative criterion having
been applied in that initial choice, but as a consequence of anisotropy in
the data. The latter would give rise to different diffraction limits in
different directions, and the choice of a single value for "the resolution"
at which the data were cut off would necessarily yield a compromise value
between the best and the worse diffraction limits. This would imply that
significant data would be excluded in the best diffracting directions, that
would subsequently drive PAIREF towards increasing the estimated resolution
compared to its compromise value.
This "hunch" was validated by a detailed comparison carried out on the
exact same examples that are considered in the 2020 paper by Maly et al.,
that is summarised in the attached PDF. In other words, whenever anisotropy
is present in the data, PAIREF will tend to indicate a higher value for an
isotropic cut-off than would have been estimated for the initial dataset.
The problem with taking the PAIREF result as the final answer is that the
higher cut-off it indicates is applied *isotropically*. The inclusion of the
significant data thus reclaimed is therefore unavoidably accompanied by that
of noisy data in the worst diffracting direction(s), resulting in alarmingly
poor statistics in the outermost shell (as pointed out in Eleanor's message)
that may cast doubts on the usefulness of the procedure. This consideration
was the basis of the rationale for implementing an *anisotropic* cut-off
surface in STARANISO, so that one could thus reclaim the significant data in
the best-diffracting direction(s) while avoiding the simultaneous inclusion
of the pure-noise measurements in the worse one(s). While this is clearly
and extensively explained in the documentation provided on the STARANISO
server [2], it seems to be far from having been assimilated. Of course this
would be perfect material for a publication, but life is somehow too short,
and our to-do list has remained too long, to leave us room for spending the
necessary time to go through the process of putting a paper together. The
truly important matter is to get our picture in front of the user community.
Now that the combined topics of PAIREF and anisotropy are being brought
to the foreground of the community's attention, this seems like the perfect
opportunity to present our analysis and position: what PAIREF achieves in
terms of an upward revision of an initial isotropic resolution cut-off is
likely to be achieved more straightforwardly by submitting the same data to
the STARANISO server (or using it within autoPROC [3]); and the STARANISO
output will have the advantage of being devoid of the large extra amount of
purely noisy, uninformative data that are retained in the output from PAIREF
according to its revised isotropic cut-off.
We would very much welcome feedback on this position: indeed we would
like to *crowd-source* the validation (or refutation) of this conclusion. In
our view, continuing to use the PAIREF procedure to revise an isotropic
resolution cut off misses the point about the consequences of anisotropy.
The only sensible use of a PAIREF-like procedure would be to adjust the
cut-off threshold for the local average of I/sig(I) in STARANISO, whose
default value is currently 1.2 but can be reset by the user through the Web
server's GUI. We occasionally see datasets of very high quality for which
the CC_1/2 value in the outermost shell stays above 0.6 or even 0.7, and it
is quite plausible that further useful data could be rescued if the local
I/sig(I) cut-off threshold were lowered below 1.2.
Concerning Eleanor's view that noisy data can't hurt refinement because
they are properly down-weighted by the consideration of e.g. Rfree values in
resolution shells, we would point out that any criterion based on statistics
in resolution shells will be polluted if the data are anisotropic and if the
noisy data that STARANISO would reject are retained. That will result in
excessive down-weighting of the significant data that STARANISO retains,
hence in losing the information they contain. Perhaps this is a matter for
later discussion, but the main idea is that retaining pure-noise data is not
neutral in refinement, and that every "isotropic thinking habit" on which
many views are based needs to be revisited.
With best wishes,
Clemens, Claus, Ian and Gerard.
[1] Tickle, I.J., Flensburg, C., Keller, P., Paciorek, W., Sharff, A.,
Vonrhein, C., Bricogne, G. (2018). STARANISO. Cambridge, United
Kingdom: Global Phasing Ltd.
https://www.jiscmail.ac.uk/cgi-bin/wa-jisc.exe?A2=ind1806&L=CCP4BB&O=D&P=3971
[2]https://staraniso.globalphasing.org/
[3]https://doi.org/10.1107/s0907444911007773
https://www.globalphasing.com/autoproc/
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Vincent Chaptal, PhD
Director of GdR APPICOM
Drug Resistance and Membrane Proteins Lab
MMSB -UMR5086
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