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Data quality: Difference between revisions
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There is not probably much reason to limit resolution by Rmerge. When the resolution limit is selected based on Rmerge being less than certain cutoff, the argument is that in higher resolution shells the variation among independent measurements of the intensity of the same reflection is too high. But such variation is bound to be high for weak reflections. Plus, factors such as redundancy may significantly affect Rmerge. Rmerge may and should be used as the measure of the overall data quality (e.g. of two independent datasets the one that has higher Rmerge probably is noisier). | There is not probably much reason to limit resolution by Rmerge. When the resolution limit is selected based on Rmerge being less than certain cutoff, the argument is that in higher resolution shells the variation among independent measurements of the intensity of the same reflection is too high. But such variation is bound to be high for weak reflections. Plus, factors such as redundancy may significantly affect Rmerge. Rmerge may and should be used as the measure of the overall data quality (e.g. of two independent datasets the one that has higher Rmerge probably is noisier). | ||
One thing you achieve by choosing resolution limit based on Rmerge (which generally means that your I/sigma in the highest resolution shell will be >4), of course, is lower R-factors in refinement. It is perfectly OK to aspire low R-factors, but to achieve this by throwing away data probably isn't. | One thing you achieve by choosing resolution limit based on Rmerge (which generally means that your <math>I/\sigma</math> in the highest resolution shell will be >4), of course, is lower R-factors in refinement. It is perfectly OK to aspire low R-factors, but to achieve this by throwing away data probably isn't. | ||