International
Tables for Crystallography Volume F Crystallography of biological macromolecules Edited by M. G. Rossmann and E. Arnold © International Union of Crystallography 2006 |
International Tables for Crystallography (2006). Vol. F, ch. 11.5, p. 238
Section 11.5.6. Estimating the quality of data scaling and averaging^{a}Department of Biological Sciences, Purdue University, West Lafayette, IN 47907-1392, USA |
A commonly used estimate of the quality of scaled and averaged Bragg reflection intensities is . Useful definitions of R factors are: The linear (R_{1}), square (R_{2}) and weighted () R factors can be subdivided into resolution ranges, intensity ranges, reflection classes, frame number and regions of the detector surface. When method 1 is used, reflections can be grouped in terms of the sums of partialities of contributing partial reflections .
The R-factor variation depends on the properties of the detector with respect to intensities. Generally the R factor decreases as intensity increases. Thus, the R factor generally increases with resolution. Any deviation from this behaviour might indicate a problem in the data collection due to nonlinearity of the detector response, ice diffuse diffraction, or any other stray effects superimposed on the crystal diffraction.
A useful indicator of the quality of the intensity estimates of partial reflections is the mean ratio of calculated partiality to observed partiality: The deviation of this ratio from unity can be examined as a function of the reflection intensity, resolution and calculated partiality.
The comparison of R factors for centric and noncentric reflections can be used to determine the significance of an anomalous-scattering effect. The quality of the anomalous-dispersion signal can be assessed by calculation of the scatter, , where and is the average of the n measurements of the full reflection intensities . The values for noncentric reflections can be compared to the scatter, or , of reflections differing only in absorption while excluding Bijvoet opposites. The mean scatter is calculated from all values, The ratios and should be larger than unity for significant anomalous-dispersion data.