[phenixbb] Rfree and a low resolution data set

[Andreas Forster]

Dear Toon,

this does't answer your question, but cutting your data at 3.6 Å is
probably not the best way of continuing.  Try processing with autoPROC or
submit the full data to the staranio server (staraniso.globalphasing.com)
to get a better representation of the extent of reciprocal space that your
experiment covers.  You will end up with more reflections for refinement
etc.

All best.


Andreas



On Wed, Apr 4, 2018 at 11:47 AM, Toon Van Thillo <
toon.vanthillo at student.kuleuven.be> wrote:

> Hi all,
>
>
> Currently I am refining a data set which showed anisotropic diffraction.
> Aimless suggested cutoffs at 2.3, 2.6 and 3.6 angstrom for the h,k and l
> axis.
>
> I chose a general 3.6 cutoff to obtain satisfactory statistics for Rmeas,
> I/sd(I) and CC1/2. At this resolution the data set consists of
> approximately 2800 reflections.
>
>
> Generally 5% of the set is set aside as the Rfree test set and I found
> that a minimum of 500 reflections in total is used to produce a reliable
> Rfree. However, 5% only amounts to 140 reflections in this case. I am
> hesitant to include more reflections as I would have to go up to 20% of the
> reflections to obtain more than 500 reflections for the test set. In a
> discussion on the CCP4 message boards some time ago it was suggested to do
> multiple refinements with different test sets:
>
> https://www.jiscmail.ac.uk/cgi-bin/webadmin?A2=ind1411&L=
> ccp4bb&F=&S=&P=125570
>
>
> In the thread it was also discussed that a least squares approach is
> prefered when using a small test set. However, when using a LS target, the
> resulting Rfree is very high (10% higher than when using the automatic
> option) and *phenix.refine*​ produces awful geometry (24% ramachandran
> outliers, 105 clashcore...). It seems that the refinement is performed
> without restraints? Optimize X-ray/stereochemistry weight does not result
> in improved stereochemistry. My question is if the LS approach is still
> relevant and if so, is there an explanation (and solution) for the bad
> statistics?
>
>
> Kind regards,
>
>
> Toon Van Thillo
>
>
>
>
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