APPLE picker: Automatic particle picking, a low-effort cryo-EM framework

J Struct Biol. 2018 Nov;204(2):215-227. doi: 10.1016/j.jsb.2018.08.012. Epub 2018 Aug 19.

Abstract

Particle picking is a crucial first step in the computational pipeline of single-particle cryo-electron microscopy (cryo-EM). Selecting particles from the micrographs is difficult especially for small particles with low contrast. As high-resolution reconstruction typically requires hundreds of thousands of particles, manually picking that many particles is often too time-consuming. While template-based particle picking is currently a popular approach, it may suffer from introducing manual bias into the selection process. In addition, this approach is still somewhat time-consuming. This paper presents the APPLE (Automatic Particle Picking with Low user Effort) picker, a simple and novel approach for fast, accurate, and template-free particle picking. This approach is evaluated on publicly available datasets containing micrographs of β-galactosidase, T20S proteasome, 70S ribosome and keyhole limpet hemocyanin projections.

Keywords: Cross-correlation; Cryo-electron microscopy; Micrographs; Particle picking; Single-particle reconstruction; Support vector machines; Template-free.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Cryoelectron Microscopy / methods*
  • Imaging, Three-Dimensional
  • Pattern Recognition, Automated
  • beta-Galactosidase / chemistry*
  • beta-Galactosidase / ultrastructure*

Substances

  • beta-Galactosidase