Linking crystallographic model and data quality.
In macromolecular x-ray crystallography, refinement R values measure the agreement between observed and calculated data. Analogously, R(merge) values reporting on the agreement between multiple measurements of a given reflection are used to assess data quality. Here, we show that despite their widespread use, R(merge) values are poorly suited for determining the high-resolution limit and that current standard protocols discard much useful data. We introduce a statistic that estimates the correlation of an observed data set with the underlying (not measurable) true signal; this quantity, CC*, provides a single statistically valid guide for deciding which data are useful. CC* also can be used to assess model and data quality on the same scale, and this reveals when data quality is limiting model improvement.
Department of Biochemistry and Biophysics, Oregon State University, Corvallis, OR 97331, USA.
P Andrew
PA
Karplus
Kay
K
Diederichs
D018360:Crystallography, X-Ray; D050558:Cysteine Dioxygenase / Q000737:chemistry*; D003627:Data Interpretation, Statistical; D008958:Models, Molecular; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry*; D012107:Research Design
D011506:Proteins; D050558:Cysteine Dioxygenase