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X-ray Crystallography

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$Microcrystallography of Protein Crystals and In Cellulo Diffraction$

Microcrystallography of Protein Crystals and In Cellulo Diffraction

Published on: July 21, 2017

Scaling diffraction data in the DIALS software package: algorithms and new approaches for multi-crystal scaling.

James Beilsten-Edmands¹, Graeme Winter¹, Richard Gildea¹

¹Diamond Light Source Ltd, Harwell Science and Innovation Campus, Didcot OX11 0DE, United Kingdom.

Acta Crystallographica. Section D, Structural Biology

|April 8, 2020

Summary

Accurate scaling of X-ray diffraction data is crucial for macromolecular crystallography. This study evaluates scaling algorithms in DIALS, enhancing multi-crystal and multi-sweep data processing for smaller samples.

Keywords:

crystallography data analysis diffraction multi-crystal scaling

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Last Updated: Dec 24, 2025

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Microfluidic Chips for In Situ Crystal X-ray Diffraction and In Situ Dynamic Light Scattering for Serial Crystallography

Published on: April 24, 2018

Area of Science:

Crystallography
Structural Biology
Data Processing

Background:

X-ray diffraction data intensities require correction for experimental variations to ensure accurate scaling.
Scaling accounts for factors like illumination, absorption, and radiation damage affecting intensity measurements.
Accurate scaling necessitates prior determination of crystal point-group symmetry.

Purpose of the Study:

To describe and evaluate scaling algorithms within the DIALS data-processing package.
To demonstrate the effectiveness of DIALS scaling on macromolecular crystallographic rotation data.
To introduce new workflows for scaling multi-crystal or multi-sweep datasets, supporting small sample analysis.

Main Methods:

Implementation and evaluation of scaling algorithms in the DIALS software.
Application to example macromolecular crystallographic rotation data.
Incorporation of a free-set validation method for model and algorithm selection.

Main Results:

Demonstrated effectiveness of DIALS scaling algorithms on experimental data.
Enabled new workflows for scaling multi-crystal and multi-sweep datasets.
Quantified the suitability of scaling models and algorithms using free-set validation.

Conclusions:

The DIALS scaling algorithms are effective for macromolecular crystallography.
These algorithms support advanced data collection strategies, particularly for small or challenging samples.
Free-set validation provides a robust method for assessing scaling quality.