Automated pipelines for rapid evaluation during cryoEM data acquisition

Abstract

Cryo-electron microscopy (cryoEM) has become a popular method for determining high-resolution structures of biomolecules. However, data processing can be time-consuming, particularly for new researchers entering the field. To improve data quality and increase data collection efficiency, several software packages have been developed for on-the-fly data processing with various degrees of automation. These software packages allow researchers to perform tasks such as motion correction, CTF estimation, 2D classification, and 3D reconstruction in real-time, with minimal human input. On-the-fly data processing can not only improve data collection efficiency but also increase the productivity of instrumentation in high demand. However, the various software packages available differ in their performance, computational requirements, and levels of automation. In this review, we describe the minimal metrics used to assess data quality during data collection, outline the features of an ideal on-the-fly data processing software systems, and provide results from using three of these systems.