2QVO.xds: Difference between revisions

correct CCmax to CC All
(correct CCmax to CC All)
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==Optimization of data reduction==
==Optimization of data reduction==


The only safe way to optimize the data reduction is to look at external quality indicators. Internal R-factors, and even the correlation coefficient of the anomalous signal are of comparatively little value. A readily available external quality indicator is CCmax/CCweak as obtained by [[ccp4com:SHELX_C/D/E|SHELXD]].
The only safe way to optimize the data reduction is to look at external quality indicators. Internal R-factors, and even the correlation coefficient of the anomalous signal are of comparatively little value. A readily available external quality indicator is CC All/CC Weak as obtained by [[ccp4com:SHELX_C/D/E|SHELXD]].


WFAC1 was already discussed above. Another candidate for optimization is MAXIMUM_ERROR_OF_SPOT_POSITION. By default this is 3.0 . In the case of these data, this default appears to be too small, because the STANDARD DEVIATION OF SPOT    POSITION (PIXELS) (as reported by IDXREF, INTEGRATE and CORRECT after refinement) is quite high (1.5 and more). This prevents XDS from using all the reflections for geometry refinement.
WFAC1 was already discussed above. Another candidate for optimization is MAXIMUM_ERROR_OF_SPOT_POSITION. By default this is 3.0 . In the case of these data, this default appears to be too small, because the STANDARD DEVIATION OF SPOT    POSITION (PIXELS) (as reported by IDXREF, INTEGRATE and CORRECT after refinement) is quite high (1.5 and more). This prevents XDS from using all the reflections for geometry refinement.


I found that MAXIMUM_ERROR_OF_SPOT_POSITION=6.0 significantly improved the internal statistics (mostly the r-factors, but not so much the correlation coefficient of the anom signal), and improved CCmax/CCweak indicators (to more than 40). SHELXE then produces significantly better and more complete models. Try for yourself!
I found that MAXIMUM_ERROR_OF_SPOT_POSITION=6.0 significantly improved the internal statistics (mostly the r-factors, but not so much the correlation coefficient of the anom signal), and improved CC All/CC Weak indicators (to more than 40). SHELXE then produces significantly better and more complete models. Try for yourself!


One thing I noticed that if I specify the known spacegroup in IDXREF then the results are worse than if the integration is performed in P1. Likewise, [[optimization]] did not work: recycling of GXPARM.XDS to use as XPARM.XDS, and thus imposing the lattice symmetry in the geometry refinement in INTEGRATE. These findings my correspond to the fact that in P1 the angles do not refine to 90.0xx or 89.9xx degrees. In other words, the metric symmetry is not as well fulfilled as it should be. This results in fairly large deviations from the ideal P42 positions; the refinement of cell parameters in P1 partly compensates for this. I have however no idea why this deviation from metric symmetry could occur.  
One thing I noticed that if I specify the known spacegroup in IDXREF then the results are worse than if the integration is performed in P1. Likewise, [[optimization]] did not work: recycling of GXPARM.XDS to use as XPARM.XDS, and thus imposing the lattice symmetry in the geometry refinement in INTEGRATE. These findings my correspond to the fact that in P1 the angles do not refine to 90.0xx or 89.9xx degrees. In other words, the metric symmetry is not as well fulfilled as it should be. This results in fairly large deviations from the ideal P42 positions; the refinement of cell parameters in P1 partly compensates for this. I have however no idea why this deviation from metric symmetry could occur.  
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