[phenixbb] refinement with translational ncs

[Pavel Afonine]

Hi Jorge,

"tncs_correction = True" is functional, somewhat tested and overall 
supposed to work. However, we have not done any large scale systematic 
tests to evaluate what exactly benefits are.

As to "what does this actually do?" -- this option treats the presence 
of tNCS as described here:

https://doi.org/10.1107/S0907444912045374

Pavel

On 1/27/21 02:46, Jorge Iulek wrote:
> Dear all,
>
>
>     I have a dataset at 2.98 A resolution, images processed to CC_1/2 
> at circa 50% in the last resolution shell, tetramer in the asymmetric 
> unit, local (rotational) symmetry 222. Xtriage indicates a peak in the 
> Patterson function at 20% height of origin peak, at fractional 
> coordinates of 0.0000 0.0000 0.3177. Space group is P21.
>
>      I am aware that this brings problems to refinement , as even 
> stated at xtriage output  "Translational pseudo-symmetry is very 
> likely present in these data.  Be aware that this will change the 
> intensity statistics and may impact subsequent  analyses, and in 
> practice may lead to higher R-factors in refinement.", and so I can't 
> lower my R and R-free below ~31 and 36 % , respectively.
>
>     At phenix.refine, setting "tncs_correction = True" brings little 
> benefit (what does this actually do? points to references are 
> welcome). I wonder nevertheless if some strategy might help in on 
> lowering these R's and, of course, allow me to build a better model 
> (in spite of the resolution). I tried some combinations of other types 
> of ncs and tls groups, with little success. Particularly, it seems 
> that the refinement of ADPs are a kind of unstable (what I would 
> understand come from the - partial - modular nature of the intensities 
> - due to tncs - and these - ADP - would be reflected by the intensity 
> fall-off with resolution). What about refining ADPs only to a zone 
> which is not affect by data modulation? How to do that? Any other ideas?
>
>     Thanks,
>
>
> Jorge
>
>
>
>
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