Flexible workflows for on‐the‐fly electron‐microscopy single‐particle image processing using Scipion. Issue 10 (7th October 2019)

• Record Type: Journal Article
• Authors: Maluenda, D.; Majtner, T.; Horvath, P.; Vilas, J. L.; Jiménez-Moreno, A.; Mota, J.; Ramírez-Aportela, E.; Sánchez-García, R.; Conesa, P.; del Caño, L.; Rancel, Y.; Fonseca, Y.; Martínez, M.; Sharov, G.; García, C.A.; Strelak, D.; Melero, R.; Marabini, R.; Carazo, J. M.; Sorzano, C. O. S.
• Is Part Of: Acta crystallographica. Volume 75:Issue 10(2019)
• Page Start: 882
• Page End: 894
• Publication Date: 2019-10-07
• Subjects: Scipion -- image processing -- electron microscopy -- single‐particle analysis -- stream processing -- electron‐microscopy facilities; X-ray crystallography -- Periodicals; Crystallography -- Periodicals; Molecular biology -- Periodicals; Molecular structure -- Periodicals; Biomolecules -- Structure -- Periodicals; Cytology -- Periodicals; Biomolecules -- Structure; Crystallography; Cytology; Molecular biology; Molecular structure; X-ray crystallography; Periodicals; 548
• DOI: 10.1107/S2059798319011860
• Languages: English
• ISSNs: 2059-7983

Abstract

Abstract : The Scipion framework allows very flexible image‐processing workflows to be generated and employed at electron‐microscopy facilities, such that image acquisition can be monitored and possible problems detected, thereby enabling early decisions to be made on the fly. The streaming workflow can be very simple or extended, permitting the data resolution and heterogeneity to be estimated and adapted to the desire of the user and the microscope operator. Abstract : Electron microscopy of macromolecular structures is an approach that is in increasing demand in the field of structural biology. The automation of image acquisition has greatly increased the potential throughput of electron microscopy. Here, the focus is on the possibilities in Scipion to implement flexible and robust image‐processing workflows that allow the electron‐microscope operator and the user to monitor the quality of image acquisition, assessing very simple acquisition measures or obtaining a first estimate of the initial volume, or the data resolution and heterogeneity, without any need for programming skills. These workflows can implement intelligent automatic decisions and they can warn the user of possible acquisition failures. These concepts are illustrated by analysis of the well known 2.2 Å resolution β‐galactosidase data set.