Scaling and assessment of data quality
Scaling and assessment of data quality
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DOI：
10.1107/s0907444905036693
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发表时间：
2006-01-01
影响因子：
2.2
通讯作者：
Evans, P
中科院分区：
文献类型：
--
作者：
Evans, P
影响测得的衍射强度的各种物理因素进行了讨论，因为是缩放模型，可用于把数据在一个一致的规模。在缩放之后，可以分析强度以设置数据集的真实的分辨率，以检测坏区域（例如，G.图像质量差），分析辐射损害和评估数据集的总体质量。任何异常信号的重要性可以通过概率和相关分析来评估。描述了CCP4定标程序SCALA所使用的算法。对强度的缩放和合并的要求是劳厄群和点群对称性的知识：衍射图案的可能对称性可以从分数（例如可能与劳厄群相关的观测之间的相关系数）确定。这些评分功能在一个新的程序POINTLESS中实现。
The various physical factors affecting measured diffraction intensities are discussed, as are the scaling models which may be used to put the data on a consistent scale. After scaling, the intensities can be analysed to set the real resolution of the data set, to detect bad regions ( e. g. bad images), to analyse radiation damage and to assess the overall quality of the data set. The significance of any anomalous signal may be assessed by probability and correlation analysis. The algorithms used by the CCP4 scaling program SCALA are described. A requirement for the scaling and merging of intensities is knowledge of the Laue group and point-group symmetries: the possible symmetry of the diffraction pattern may be determined from scores such as correlation coefficients between observations which might be symmetry-related. These scoring functions are implemented in a new program POINTLESS.