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Real-time cryo-electron microscopy data preprocessing with Warp.

Dimitry TegunovPatrick Cramer
Published in: Nature methods (2019)
The acquisition of cryo-electron microscopy (cryo-EM) data from biological specimens must be tightly coupled to data preprocessing to ensure the best data quality and microscope usage. Here we describe Warp, a software that automates all preprocessing steps of cryo-EM data acquisition and enables real-time evaluation. Warp corrects micrographs for global and local motion, estimates the local defocus and monitors key parameters for each recorded micrograph or tomographic tilt series in real time. The software further includes deep-learning-based models for accurate particle picking and image denoising. The output from Warp can be fed into established programs for particle classification and 3D-map refinement. Our benchmarks show improvement in the nominal resolution, which went from 3.9 Å to 3.2 Å, of a published cryo-EM data set for influenza virus hemagglutinin. Warp is easy to install from http://github.com/cramerlab/warp and computationally inexpensive, and has an intuitive, streamlined user interface.
Keyphrases
  • electron microscopy
  • electronic health record
  • deep learning
  • big data
  • machine learning
  • high resolution
  • data analysis
  • public health
  • randomized controlled trial
  • mass spectrometry
  • high speed
  • high density