Data Quality Analysis
Data collection at a home source or at a synchrotron is the last truly experimental step in the structure solution process and achieving good quality diffraction data is crucial for solving the phase problem and getting reliable three-dimensional positions of atoms in a protein. Any errors introduced during this step of the experiment will affect any downstream analysis and often influence the success or failure of the structure solution process. In the process of scaling and merging intensities, a series of metrics are generated which give indications about the general quality of the data, and of specific problems in parts of it, notably the maximum effective resolution of the data, and the presence of radiation damage. The most common effects which introduce errors to diffraction data are detailed and general practical approaches will be presented which may be used to minimise errors and improve the quality of diffraction data, which in turn increases the ease and likelihood of solving the phase problem.