Physics

Pattern recognition (psychology)

Preprocessor

Operating system

Optics

Computer graphics (images)

Microscopy

Data acquisition

Artificial intelligence

Cryo-electron microscopy

Programming language

Software

Computer science

Nuclear magnetic resonance

Computer vision

Nature Methods

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. The user-friendly software tool Warp enables automated, on-the-fly preprocessing of cryo-EM data, including motion correction, defocus estimation, particle picking and image denoising.

Real-time cryo-electron microscopy data preprocessing with Warp