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Methods for merging data sets in electron cryo‐microscopy
Author(s) -
Wilkinson Max E.,
Kumar Ananthanarayanan,
Casañal Ana
Publication year - 2019
Publication title -
acta crystallographica section d
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 7.374
H-Index - 138
ISSN - 2059-7983
DOI - 10.1107/s2059798319010519
Subject(s) - cryo electron microscopy , flexibility (engineering) , computer science , microscopy , data mining , artificial intelligence , optics , physics , mathematics , statistics , nuclear magnetic resonance
Recent developments have resulted in electron cryo‐microscopy (cryo‐EM) becoming a useful tool for the structure determination of biological macromolecules. For samples containing inherent flexibility, heterogeneity or preferred orientation, the collection of extensive cryo‐EM data using several conditions and microscopes is often required. In such a scenario, merging cryo‐EM data sets is advantageous because it allows improved three‐dimensional reconstructions to be obtained. Since data sets are not always collected with the same pixel size, merging data can be challenging. Here, two methods to combine cryo‐EM data are described. Both involve the calculation of a rescaling factor from independent data sets. The effects of errors in the scaling factor on the results of data merging are also estimated. The methods described here provide a guideline for cryo‐EM users who wish to combine data sets from the same type of microscope and detector.