CryoSPARC Guide
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  • Cryo-EM Foundations
    • Image Formation
      • Contrast in Cryo-EM
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  • Expectation Maximization in Cryo-EM
  • Processing Data in cryoSPARC
    • Get Started with CryoSPARC: Introductory Tutorial (v4.0+)
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    • All Job Types in CryoSPARC
      • Import
        • Job: Import Movies
        • Job: Import Micrographs
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        • Job: Import Result Group
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      • Motion Correction
        • Job: Patch Motion Correction
        • Job: Full-Frame Motion Correction
        • Job: Local Motion Correction
        • Job: MotionCor2 (Wrapper) (BETA)
        • Job: Reference Based Motion Correction (BETA)
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        • Job: Patch CTF Estimation
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          • T20S Proteasome: Deep Particle Picking Tutorial
          • Job: Deep Picker Train and Job: Deep Picker Inference
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        • Job: Sharpening Tools
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        • Job: Local Resolution Estimation
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        • Job: Local Refinement
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        • Job: Local Refinement (Legacy)
      • Helical Reconstruction
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        • Job: Exposure Sets Tool
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        • Job: Split Volumes Group
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    • CryoSPARC Tools
    • Data Processing Tutorials
      • Case study: End-to-end processing of a ligand-bound GPCR (EMPIAR-10853)
      • Case Study: DkTx-bound TRPV1 (EMPIAR-10059)
      • Case Study: Pseudosymmetry in TRPV5 and Calmodulin (EMPIAR-10256)
      • Case Study: End-to-end processing of an inactive GPCR (EMPIAR-10668)
      • Case Study: End-to-end processing of encapsulated ferritin (EMPIAR-10716)
      • Case Study: Exploratory data processing by Oliver Clarke
      • Tutorial: Tips for Membrane Protein Structures
      • Tutorial: Common CryoSPARC Plots
      • Tutorial: Negative Stain Data
      • Tutorial: Phase Plate Data
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      • Case Study: Yeast U4/U6.U5 tri-snRNP
      • Tutorial: 3D Classification
      • Tutorial: 3D Variability Analysis (Part One)
      • Tutorial: 3D Variability Analysis (Part Two)
      • Tutorial: 3D Flexible Refinement
        • Installing 3DFlex Dependencies (v4.1–v4.3)
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  • Real-time processing in cryoSPARC Live
    • About CryoSPARC Live
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  • Resources
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On this page
  • At a Glance
  • Description
  • Inputs
  • Movies
  • Particles
  • Commonly Adjusted Parameters
  • Only process this many movies
  • Save results in 16-bit floating point
  • Override e/A^2/frame
  • Extraction box size
  • Fourier crop to box size (pix)
  • Outputs
  • Particles extracted
  • Diagnostic plots
  • Common Next Steps
  • Recommended Alternatives
  • References
  1. Processing Data in cryoSPARC
  2. All Job Types in CryoSPARC
  3. Motion Correction

Job: Local Motion Correction

Local motion correction.

PreviousJob: Full-Frame Motion CorrectionNextJob: MotionCor2 (Wrapper) (BETA)

Last updated 11 months ago

At a Glance

Track and correct the motion of individual particles in movies.

Description

Local Motion Correction job corrects beam-induced motion on a per-particle basis, taking full-frame-motion corrected movies and particle pick locations as inputs. A square patch around each particle is extracted from each frame of the movie. The trajectory of these patches is modeled and then used to extract a motion-corrected patch for each particle and each frame. Local motion correction also applies . Local motion correction is based on alignparts_lbfgs (Rubinstein et al. 2015).

Two versions of Local Motion Correction are available - Local Motion Correction runs on a single GPU, while Local Motion Correction (Multi-GPU) uses multiple available GPUs to parallelize processing.

This job does not require a high-quality 3D reference volume (unlike Reference Based Motion Correction), but it does require well-centered particle picks. A typical workflow would be to first use patch motion correction on the raw movies, perform picking, and then re-perform motion correction with Local motion correction.

See for more details about the different types of motion correction available in CryoSPARC.

Inputs

Movies

Local motion correction requires raw movies in .mrc , .tif , .eer, or .mrc.bz2 format, typically from an Import Movies job.

Particles

Particles should be well-centered and relatively clean of junk or empty picks, most often from a 2D Classification or any 3D refinement job.

Commonly Adjusted Parameters

Only process this many movies

This parameter selects the first n movies to process, rather than the entire input stack. It is most useful when working with a subset of movies to assess data quality before committing to a full processing pipeline.

If collection parameters changed during the collection, it may be better to use Exposure Sets to select a random subset instead.

Save results in 16-bit floating point

Override e/A^2/frame

When Apply exposure weighting is enabled, this parameter can be used to override the exposure level of the movie data, in case the level was not correctly set at import time. In contrast to the Import Movies job's Total exposure dose (e/A^2) parameter, Local Motion Correction's parameter must be specified per-frame. Exposure weighting is based on the reference curves from Grant and Grigorieff.

Extraction box size

The side length of the extraction box, in pixels. The general rule of thumb is twice the width of the particle, but more precise guidance is given by Rosenthal and Henderson as

Box Size (A˚)=d + (2λ×δr)\mathrm{Box\ Size\ (\AA{})} = d\ +\ (2\lambda{}\times{}\frac{\delta{}}{r})Box Size (A˚)=d + (2λ×rδ​)

where

  • d is the particle diameter in Å,

  • λ is the electron wavelength (approximately 0.020 Å and 0.025 Å for 300 kV and 200 kV microscopes, respectively),

  • δ is the defocus (in Å, not μm), and

  • r is the expected resolution of the final reconstruction (the average CTF fit would be a good starting value if data quality is not known)

The first term of this equation is simply the particle diameter, an obvious lower limit on box size, since the entire particle must fit in the box. The second term models the displacement of signal by the CTF. With higher defocus, higher frequency information is displaced by a greater distance, hence the direct dependence on defocus and inverse dependence on final resolution, since higher resolution decreases r.

Fourier crop to box size (pix)

Extracted, motion-corrected particle images will be Fourier cropped to this box size.

Outputs

Particles extracted

Since particle locations are already known and motion of the entire movie is not modeled, this job outputs motion corrected particle images rather than whole micrographs.

Diagnostic plots

Local Motion Correction also produces a plot of the modeled movement of each particle:

The local motion plot shows the motion modeled for each particle patch. The trajectories are scaled by 40x to be visible on the micrograph scale.

The grey line shows the raw trajectory. Because single-particle data typically has a very poor signal-to-noise ratio, these trajectories are very noisy and likely not a good representation of the true movement of the particle. The per-frame trajectory is therefore smoothed out to produce the final result. This smooth trajectory is in red.

Common Next Steps

Particle images from Local Motion Correction are suitable for use in a variety of jobs, including 3D Refinements and heterogeneity analysis techniques.

Recommended Alternatives

References

  1. Rubinstein JL, Brubaker MA. Alignment of cryo-EM movies of individual particles by optimization of image translations. J Struct Biol (2015).

  2. Rosenthal, P. B. & Henderson, R. Optimal Determination of Particle Orientation, Absolute Hand, and Contrast Loss in Single-particle Electron Cryomicroscopy. Journal of Molecular Biology 333, 721–745 (2003).

  3. Grant, T. & Grigorieff, N. Measuring the optimal exposure for single particle cryo-EM using a 2.6 Å reconstruction of rotavirus VP6. eLife 4, e06980 (2015).

Saves the output micrographs in 16-bit floating point. We recommend that this option is turned on to save space at minimal loss of accuracy. See the for more information.

If a high-quality reconstruction is available for the dataset, will likely perform better than Local Motion Correction. Like Local Motion Correction, it directly models particle trajectories. However, Reference Based Motion Correction also calculates empirical dose weights (rather than use the reference curves), which can lead to improved final reconstruction quality.

A table of electron wavelengths for a given accelerating voltage can be found here:

16-bit floating point article
Reference Based Motion Correction
https://www.jeol.com/words/emterms/20121023.071258.php#gsc.tab=0
Motion Correction
Dose Weighting