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Updated: Jun 16, 2026

A User-friendly and Powerful R Analysis of Large-scale Datasets
Published on: November 4, 2025
Robust indexing for automatic data collection
Nicholas K Sauter1, Ralf W Grosse-Kunstleve, Paul D Adams
1Department of Physical Biosciences, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Bldg 4R0230, Berkeley, CA 94720, USA.
Abstract:
Improved methods for indexing diffraction patterns from macromolecular crystals are presented. The novel procedures include a more robust way to verify the position of the incident X-ray beam on the detector, an algorithm to verify that the deduced lattice basis is consistent with the observations, and an alternative approach to identify the metric symmetry of the lattice. These methods help to correct failures commonly experienced during indexing, and increase the overall success rate of the process. Rapid indexing, without the need for visual inspection, will play an important role as beamlines at synchrotron sources prepare for high-throughput automation.
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