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International
Tables for Crystallography Volume F Crystallography of biological macromolecules Edited by M. G. Rossman and E. Arnold © International Union of Crystallography 2006 |
International Tables for Crystallography (2006). Vol. F. ch. 18.1, p. 374
Section 18.1.9.3. R and Rfree
a
San Diego Supercomputer Center 0505, University of California at San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0505, USA, and bStructural, Analytical and Medicinal Chemistry, Pharmacia & Upjohn, Inc., Kalamazoo, MI 49001-0119, USA |
Cross validation is a powerful tool for avoiding over-interpretation of the data by a too elaborate model. The introduction of cross validation to crystallography (Brünger, 1992![[link]](/graphics/greenarr.gif)
) has been responsible for significant improvement in the quality of structure determinations. A subset of the reflections, chosen randomly, is segregated and not used in the refinement. If the model is correct and the only errors are statistical, these reflections should have an R factor close to that of the reflections used in the refinement. Changes to the model should affect both R and Rfree similarly. Kleywegt & Jones (1997) have pointed out that it is necessary to treat the selection of free reflections very carefully in the presence of noncrystallographic symmetry.
References
Brünger, A. T. (1992). Free R-value – a novel statistical quantity for assessing the accuracy of crystal structures. Nature (London), 355, 472–475.Google Scholar
Kleywegt, G. J. & Jones, T. A. (1997). Model building and refinement practice. Methods Enzymol. 277, 208–230.Google Scholar
