Background modelling of diffraction data in the presence of ice rings

IUCrJ

Evans, G.¹  Gildea, R.J.²  Fuentes-Montero, L.²  Vollmar, M.²  Parkhurst, J.M.²  Waterman, D.G.³  Thorn, A.⁴  Winter, G.⁴  Murshudov, G.N.⁵ 

[1] CCP4, Research Complex at Harwell, Rutherford Appleton Laboratory, Didcot OX11 0FA, England;Diamond Light Source Ltd, Harwell Science and Innovation Campus, Didcot OX11 0DE, England;Hamburg Centre for Ultrafast Imaging, Universität Hamburg, Luruper Chaussee 149, 22761 Hamburg, Germany;Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, England;STFC Rutherford Appleton Laboratory, Didcot OX11 0FA, England

关键词: PROTEIN STRUCTURE;    REFINEMENT;    X-RAY CRYSTALLOGRAPHY;    ICE RINGS;    DATA PROCESSING;    DATA ANALYSIS;    X-RAY DIFFRACTION;    DATA QUALITY;    AUSPEX;    DIALS;   

DOI  :  10.1107/S2052252517010259

学科分类：数学（综合）

来源: International Union of Crystallography

【 摘 要 】

An algorithm for modelling the background for each Bragg reflection in a series of X-ray diffraction images containing Debye–Scherrer diffraction from ice in the sample is presented. The method involves the use of a global background model which is generated from the complete X-ray diffraction data set. Fitting of this model to the background pixels is then performed for each reflection independently. The algorithm uses a static background model that does not vary over the course of the scan. The greatest improvement can be expected for data where ice rings are present throughout the data set and the local background shape at the size of a spot on the detector does not exhibit large time-dependent variation. However, the algorithm has been applied to data sets whose background showed large pixel variations (variance/mean > 2) and has been shown to improve the results of processing for these data sets. It is shown that the use of a simple flat-background model as in traditional integration programs causes systematic bias in the background determination at ice-ring resolutions, resulting in an overestimation of reflection intensities at the peaks of the ice rings and an underestimation of reflection intensities either side of the ice ring. The new global background-model algorithm presented here corrects for this bias, resulting in a noticeable improvement in R factors following refinement.

【 授权许可】

CC BY