期刊
NATURE METHODS
卷 16, 期 11, 页码 1146-+出版社
NATURE PORTFOLIO
DOI: 10.1038/s41592-019-0580-y
关键词
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资金
- ERC Advanced Grant TRANSREGULON of the European Research Council [693023]
- Deutsche Forschungsgemeinschaft [SFB 860]
- Volkswagen Foundation
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 angstrom to 3.2 angstrom, 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.
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