xia2.multiplex: a multi‐crystal data‐analysis pipeline

In macromolecular crystallography, radiation damage limits the amount of data that can be collected from a single crystal. It is often necessary to merge data sets from multiple crystals; for example, small‐wedge data collections from micro‐crystals, in situ room‐temperature data collections and dat...

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Published in:Acta crystallographica. Section D, Structural biology Vol. 78; no. 6; pp. 752 - 769
Main Authors: Gildea, Richard J., Beilsten-Edmands, James, Axford, Danny, Horrell, Sam, Aller, Pierre, Sandy, James, Sanchez-Weatherby, Juan, Owen, C. David, Lukacik, Petra, Strain-Damerell, Claire, Owen, Robin L., Walsh, Martin A., Winter, Graeme
Format: Journal Article
Language:English
Published: 5 Abbey Square, Chester, Cheshire CH1 2HU, England International Union of Crystallography 01.06.2022
Subjects:
COVID-19
Crystallography, X-Ray
Data Analysis
data processing
Humans
Macromolecular Substances - chemistry
multi‐crystal data sets
partial data sets
Research Papers
SARS-CoV-2
xia2.multiplex
partial data sets
xia2.multiplex
SARS-CoV-2
multi-crystal data sets
data analysis
data processing
ISSN:2059-7983, 2059-7983
Online Access:Get full text
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Summary:In macromolecular crystallography, radiation damage limits the amount of data that can be collected from a single crystal. It is often necessary to merge data sets from multiple crystals; for example, small‐wedge data collections from micro‐crystals, in situ room‐temperature data collections and data collection from membrane proteins in lipidic mesophases. Whilst the indexing and integration of individual data sets may be relatively straightforward with existing software, merging multiple data sets from small wedges presents new challenges. The identification of a consensus symmetry can be problematic, particularly in the presence of a potential indexing ambiguity. Furthermore, the presence of non‐isomorphous or poor‐quality data sets may reduce the overall quality of the final merged data set. To facilitate and help to optimize the scaling and merging of multiple data sets, a new program, xia2.multiplex, has been developed which takes data sets individually integrated with DIALS and performs symmetry analysis, scaling and merging of multi‐crystal data sets. xia2.multiplex also performs analysis of various pathologies that typically affect multi‐crystal data sets, including non‐isomorphism, radiation damage and preferential orientation. After the description of a number of use cases, the benefit of xia2.multiplex is demonstrated within a wider autoprocessing framework in facilitating a multi‐crystal experiment collected as part of in situ room‐temperature fragment‐screening experiments on the SARS‐CoV‐2 main protease. A new program, xia2.multiplex, has been developed to facilitate symmetry analysis, scaling and merging of multi‐crystal data sets.
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ISSN:2059-7983
2059-7983
DOI:10.1107/S2059798322004399