RELION-3: new tools for automated high-resolution cryo-EM structure determination

TLDR: The third major release of RELION as mentioned in this paper has been added in addition to GPU support, which provides flexibility in use of resources and avoids memory limitations Reference-free autopicking with Laplacian-of-Gaussian filtering and execution of jobs from python allows non-interactive processing during acquisition, including 2D-classification, de novo model generation and 3D classification Per-particle refinement of CTF parameters and correction of estimated beam tilt provides higher-resolution reconstructions when particles are at different heights in the ice, and/or coma-free alignment has not

Abstract: Here, we describe the third major release of RELION CPU-based vector acceleration has been added in addition to GPU support, which provides flexibility in use of resources and avoids memory limitations Reference-free autopicking with Laplacian-of-Gaussian filtering and execution of jobs from python allows non-interactive processing during acquisition, including 2D-classification, de novo model generation and 3D-classification Per-particle refinement of CTF parameters and correction of estimated beam tilt provides higher-resolution reconstructions when particles are at different heights in the ice, and/or coma-free alignment has not been optimal Ewald sphere curvature correction improves resolution for large particles We illustrate these developments with publicly available data sets: together with a Bayesian approach to beam-induced motion correction it leads to resolution improvements of 02-07 A compared to previous RELION versions