Publikation: Improved R-factors for diffraction data analysis in macromolecular crystallography
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1997
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Karplus, P. Andrew
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Nature Structural Biology. 1997, 4(4), pp. 269-275. ISSN 1072-8368. Available under: doi: 10.1038/nsb0497-269
Zusammenfassung
The quantity Rsym (also called Rmerge) is almost universally used for describing X-ray diffraction data quality. Here, we prove that Rsym is seriously flawed, because it has an implicit dependence on the redundancy of the data. A corrected R-factor, Rmeas' is introduced as the equivalent robust indicator of data consistency. In addition, we introduce Rmrgd' an R-factor that reflects the gain in accuracy upon averaging of equivalent reflections, as a useful indicator of the quality of reduced data. These new data quality indicators better reveal the benefits of highly redundant data and should stimulate improvements in data quality through increased merging of data from multiple crystals.
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570 Biowissenschaften, Biologie
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DIEDERICHS, Kay, P. Andrew KARPLUS, 1997. Improved R-factors for diffraction data analysis in macromolecular crystallography. In: Nature Structural Biology. 1997, 4(4), pp. 269-275. ISSN 1072-8368. Available under: doi: 10.1038/nsb0497-269BibTex
@article{Diederichs1997Impro-7948,
year={1997},
doi={10.1038/nsb0497-269},
title={Improved R-factors for diffraction data analysis in macromolecular crystallography},
number={4},
volume={4},
issn={1072-8368},
journal={Nature Structural Biology},
pages={269--275},
author={Diederichs, Kay and Karplus, P. Andrew}
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<dcterms:abstract xml:lang="eng">The quantity Rsym (also called Rmerge) is almost universally used for describing X-ray diffraction data quality. Here, we prove that Rsym is seriously flawed, because it has an implicit dependence on the redundancy of the data. A corrected R-factor, Rmeas' is introduced as the equivalent robust indicator of data consistency. In addition, we introduce Rmrgd' an R-factor that reflects the gain in accuracy upon averaging of equivalent reflections, as a useful indicator of the quality of reduced data. These new data quality indicators better reveal the benefits of highly redundant data and should stimulate improvements in data quality through increased merging of data from multiple crystals.</dcterms:abstract>
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