Cryogenic electron microscopy (Cryo-EM) has been established as one of the key players in structural biology. It can reconstruct a 3D model of a sample at a near-atomic resolution. With the increasing number of facilities, faster microscopes, and new imaging techniques, there is a growing demand for algorithms and programs able to process the so-called movie data produced by the microscopes in real time while preserving a high resolution and maximal information. In this article, we conduct a comparative analysis of the quality and performance of the most commonly used software for movie alignment. More precisely, we compare the most recent versions of FlexAlign (Xmipp v3.23.03), MotionCor2 (v1.6.4), Relion MotionCor (v4.0-beta), Warp (v1.0.9), and CryoSPARC (v4.0.3). We tested the quality of the alignment using generated phantom data, as well as real datasets, comparing the alignment precision, power spectra density, and performance scaling of each program.

• Klíčová slova
• Cryo-EM, CryoSPARC, FlexAlign, MotionCor2, Relion MotionCor, Warp, movie alignment, performance,
• Publikační typ
• časopisecké články MeSH

Image-processing pipelines require the design of complex workflows combining many different steps that bring the raw acquired data to a final result with biological meaning. In the image-processing domain of cryo-electron microscopy single-particle analysis (cryo-EM SPA), hundreds of steps must be performed to obtain the three-dimensional structure of a biological macromolecule by integrating data spread over thousands of micrographs containing millions of copies of allegedly the same macromolecule. The execution of such complicated workflows demands a specific tool to keep track of all these steps performed. Additionally, due to the extremely low signal-to-noise ratio (SNR), the estimation of any image parameter is heavily affected by noise resulting in a significant fraction of incorrect estimates. Although low SNR and processing millions of images by hundreds of sequential steps requiring substantial computational resources are specific to cryo-EM, these characteristics may be shared by other biological imaging domains. Here, we present Scipion, a Python generic open-source workflow engine specifically adapted for image processing. Its main characteristics are: (a) interoperability, (b) smart object model, (c) gluing operations, (d) comparison operations, (e) wide set of domain-specific operations, (f) execution in streaming, (g) smooth integration in high-performance computing environments, (h) execution with and without graphical capabilities, (i) flexible visualization, (j) user authentication and private access to private data, (k) scripting capabilities, (l) high performance, (m) traceability, (n) reproducibility, (o) self-reporting, (p) reusability, (q) extensibility, (r) software updates, and (s) non-restrictive software licensing.

• Klíčová slova
• cryo-EM, extensible, integration, multidomain, software-framework, workflows,
• Publikační typ
• časopisecké články MeSH