DoG Picker and TiltPicker: Software tools to facilitate particle selection in single particle electron microscopy

N. R. Voss, C. K. Yoshioka, M. Radermacher, C. S. Potter, B. Carragher

Research output: Contribution to journalArticlepeer-review

425 Scopus citations

Abstract

Solving the structure of macromolecular complexes using transmission electron microscopy can be an arduous task. Many of the steps in this process rely strongly on the aid of pre-existing structural knowledge, and are greatly complicated when this information is unavailable. Here, we present two software tools meant to facilitate particle picking, an early stage in the single-particle processing of unknown macromolecules. The first tool, DoG Picker, is an efficient and reasonably general, particle picker based on the Difference of Gaussians (DoG) image transform. It can function alone, as a reference-free particle picker with the unique ability to sort particles based on size, or it can also be used as a way to bootstrap the creation of templates or training datasets for other particle pickers. The second tool is TiltPicker, an interactive graphical interface application designed to streamline the selection of particle pairs from tilted-pair datasets. In many respects, TiltPicker is a re-implementation of the SPIDER WEB tilted-particle picker, but built on modern computer frameworks making it easier to deploy and maintain. The TiltPicker program also includes several useful new features beyond those of its predecessor.

Original languageEnglish (US)
Pages (from-to)205-213
Number of pages9
JournalJournal of Structural Biology
Volume166
Issue number2
DOIs
StatePublished - May 2009
Externally publishedYes

Keywords

  • Cryo-electron microscopy
  • Orthogonal tilt reconstruction
  • Particle picking
  • Random conical tilt
  • TEM

ASJC Scopus subject areas

  • Structural Biology

Fingerprint

Dive into the research topics of 'DoG Picker and TiltPicker: Software tools to facilitate particle selection in single particle electron microscopy'. Together they form a unique fingerprint.

Cite this