CryoSPARC Guide
  • About CryoSPARC
  • Current Version
  • Licensing
    • Non-commercial license agreement
  • Setup, Configuration and Management
    • CryoSPARC Architecture and System Requirements
    • CryoSPARC Installation Prerequisites
    • How to Download, Install and Configure
      • Obtaining A License ID
      • Downloading and Installing CryoSPARC
      • CryoSPARC Cluster Integration Script Examples
      • Accessing the CryoSPARC User Interface
    • Deploying CryoSPARC on AWS
      • Performance Benchmarks
    • Using CryoSPARC with Cluster Management Software
    • Software Updates and Patches
    • Management and Monitoring
      • Environment variables
      • (Optional) Hosting CryoSPARC Through a Reverse Proxy
      • cryosparcm reference
      • cryosparcm cli reference
      • cryosparcw reference
    • Software System Guides
      • Guide: Updating to CryoSPARC v4
      • Guide: Installation Testing with cryosparcm test
      • Guide: Verify CryoSPARC Installation with the Extensive Validation Job (v4.3+)
      • Guide: Verify CryoSPARC Installation with the Extensive Workflow (≤v4.2)
      • Guide: Performance Benchmarking (v4.3+)
      • Guide: Download Error Reports
      • Guide: Maintenance Mode and Configurable User Facing Messages
      • Guide: User Management
      • Guide: Multi-user Unix Permissions and Data Access Control
      • Guide: Lane Assignments and Restrictions
      • Guide: Queuing Directly to a GPU
      • Guide: Priority Job Queuing
      • Guide: Configuring Custom Variables for Cluster Job Submission Scripts
      • Guide: SSD Particle Caching in CryoSPARC
      • Guide: Data Management in CryoSPARC (v4.0+)
      • Guide: Data Cleanup (v4.3+)
      • Guide: Reduce Database Size (v4.3+)
      • Guide: Data Management in CryoSPARC (≤v3.3)
      • Guide: CryoSPARC Live Session Data Management
      • Guide: Manipulating .cs Files Created By CryoSPARC
      • Guide: Migrating your CryoSPARC Instance
      • Guide: EMDB-friendly XML file for FSC plots
    • Troubleshooting
  • Application Guide (v4.0+)
    • A Tour of the CryoSPARC Interface
    • Browsing the CryoSPARC Instance
    • Projects, Workspaces and Live Sessions
    • Jobs
    • Job Views: Cards, Tree, and Table
    • Creating and Running Jobs
    • Low Level Results Interface
    • Filters and Sorting
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    • Managing Data
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    • Instance Management
    • Admin Panel
  • Cryo-EM Foundations
    • Image Formation
      • Contrast in Cryo-EM
      • Waves as Vectors
      • Aliasing
  • Expectation Maximization in Cryo-EM
  • Processing Data in cryoSPARC
    • Get Started with CryoSPARC: Introductory Tutorial (v4.0+)
    • Tutorial Videos
    • All Job Types in CryoSPARC
      • Import
        • Job: Import Movies
        • Job: Import Micrographs
        • Job: Import Particle Stack
        • Job: Import 3D Volumes
        • Job: Import Templates
        • Job: Import Result Group
        • Job: Import Beam Shift
      • 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)
      • CTF Estimation
        • Job: Patch CTF Estimation
        • Job: Patch CTF Extraction
        • Job: CTFFIND4 (Wrapper)
        • Job: Gctf (Wrapper) (Legacy)
      • Exposure Curation
        • Job: Micrograph Denoiser (BETA)
        • Job: Micrograph Junk Detector (BETA)
        • Interactive Job: Manually Curate Exposures
      • Particle Picking
        • Interactive Job: Manual Picker
        • Job: Blob Picker
        • Job: Template Picker
        • Job: Filament Tracer
        • Job: Blob Picker Tuner
        • Interactive Job: Inspect Particle Picks
        • Job: Create Templates
      • Extraction
        • Job: Extract from Micrographs
        • Job: Downsample Particles
        • Job: Restack Particles
      • Deep Picking
        • Guideline for Supervised Particle Picking using Deep Learning Models
        • Deep Network Particle Picker
          • T20S Proteasome: Deep Particle Picking Tutorial
          • Job: Deep Picker Train and Job: Deep Picker Inference
        • Topaz (Bepler, et al)
          • T20S Proteasome: Topaz Particle Picking Tutorial
          • T20S Proteasome: Topaz Micrograph Denoising Tutorial
          • Job: Topaz Train and Job: Topaz Cross Validation
          • Job: Topaz Extract
          • Job: Topaz Denoise
      • Particle Curation
        • Job: 2D Classification
        • Interactive Job: Select 2D Classes
        • Job: Reference Based Auto Select 2D (BETA)
        • Job: Reconstruct 2D Classes
        • Job: Rebalance 2D Classes
        • Job: Class Probability Filter (Legacy)
        • Job: Rebalance Orientations
        • Job: Subset Particles by Statistic
      • 3D Reconstruction
        • Job: Ab-Initio Reconstruction
      • 3D Refinement
        • Job: Homogeneous Refinement
        • Job: Heterogeneous Refinement
        • Job: Non-Uniform Refinement
        • Job: Homogeneous Reconstruction Only
        • Job: Heterogeneous Reconstruction Only
        • Job: Homogeneous Refinement (Legacy)
        • Job: Non-uniform Refinement (Legacy)
      • CTF Refinement
        • Job: Global CTF Refinement
        • Job: Local CTF Refinement
        • Job: Exposure Group Utilities
      • Conformational Variability
        • Job: 3D Variability
        • Job: 3D Variability Display
        • Job: 3D Classification
        • Job: Regroup 3D Classes
        • Job: Reference Based Auto Select 3D (BETA)
        • Job: 3D Flexible Refinement (3DFlex) (BETA)
      • Postprocessing
        • Job: Sharpening Tools
        • Job: DeepEMhancer (Wrapper)
        • Job: Validation (FSC)
        • Job: Local Resolution Estimation
        • Job: Local Filtering
        • Job: ResLog Analysis
        • Job: ThreeDFSC (Wrapper) (Legacy)
      • Local Refinement
        • Job: Local Refinement
        • Job: Particle Subtraction
        • Job: Local Refinement (Legacy)
      • Helical Reconstruction
        • Helical symmetry in CryoSPARC
        • Job: Helical Refinement
        • Job: Symmetry search utility
        • Job: Average Power Spectra
      • Utilities
        • Job: Exposure Sets Tool
        • Job: Exposure Tools
        • Job: Generate Micrograph Thumbnails
        • Job: Cache Particles on SSD
        • Job: Check for Corrupt Particles
        • Job: Particle Sets Tool
        • Job: Reassign Particles to Micrographs
        • Job: Remove Duplicate Particles
        • Job: Symmetry Expansion
        • Job: Volume Tools
        • Job: Volume Alignment Tools
        • Job: Align 3D maps
        • Job: Split Volumes Group
        • Job: Orientation Diagnostics
      • Simulations
        • Job: Simulate Data (GPU)
        • Job: Simulate Data (Legacy)
    • 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
      • Tutorial: EER File Support
      • Tutorial: EPU AFIS Beam Shift Import
      • Tutorial: Patch Motion and Patch CTF
      • Tutorial: Float16 Support
      • Tutorial: Particle Picking Calibration
      • Tutorial: Blob Picker Tuner
      • Tutorial: Helical Processing using EMPIAR-10031 (MAVS)
      • Tutorial: Maximum Box Sizes for Refinement
      • Tutorial: CTF Refinement
      • Tutorial: Ewald Sphere Correction
      • Tutorial: Symmetry Relaxation
      • Tutorial: Orientation Diagnostics
      • Tutorial: BILD files in CryoSPARC v4.4+
      • Tutorial: Mask Creation
      • 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)
      • Tutorial: 3D Flex Mesh Preparation
    • Webinar Recordings
  • Real-time processing in cryoSPARC Live
    • About CryoSPARC Live
    • Prerequisites and Compute Resources Setup
    • How to Access cryoSPARC Live
    • UI Overview
    • New Live Session: Start to Finish Guide
    • CryoSPARC Live Tutorial Videos
    • Live Jobs and Session-Level Functions
    • Performance Metrics
    • Managing a CryoSPARC Live Session from the CLI
    • FAQs and Troubleshooting
  • Guides for v3
    • v3 User Interface Guide
      • Dashboard
      • Project and Workspace Management
      • Create and Build Jobs
      • Queue Job, Inspect Job and Other Job Actions
      • View and Download Results
      • Job Relationships
      • Resource Manager
      • User Management
    • Tutorial: Job Builder
    • Get Started with CryoSPARC: Introductory Tutorial (v3)
    • Tutorial: Manually Curate Exposures (v3)
  • Resources
    • Questions and Support
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  • Description
  • Input
  • Common Parameters
  • Output
  • Notes
  • Common Next Steps
  1. Processing Data in cryoSPARC
  2. All Job Types in CryoSPARC
  3. 3D Refinement

Job: Homogeneous Refinement (Legacy)

Homogeneous refinement (Legacy).

PreviousJob: Heterogeneous Reconstruction OnlyNextJob: Non-uniform Refinement (Legacy)

Last updated 5 months ago

Description

Rapidly refine a single homogeneous structure, using a particle stack an initial reference, to high-resolution and validate using the gold-standard FSC. Note: An updated version of this job is available, , that supports higher-order CTF aberrations and optimized GPU kernels.

Input

  • Particles

  • Initial model

  • Mask (optional)

Common Parameters

  • Refinement box size (Voxels): This determines the size of the internally stored volume. If this is null, the full particle size is used, otherwise images are automatically downsampled. This can be decreased to reduce memory requirements and increase speed, at the expense of omitting higher-resolution information.

  • Symmetry: This is the symmetry string corresponding to the enforced point-group symmetry to use during refinement. The allowed point group symmetry enforced are:

    • Cyclic (Cn, e.g. C2, C6, etc.)

    • Dihedral (Dn, e.g. D4, D7, etc.)

    • Tetrahedral (T)

    • Octahedral (O)

    • Icosahedral (I)

  • Re-estimate greyscale level of input reference: This can be enabled to estimate the multiplicative factor that correctly re-scales the reference to match the greyscale of the images. It is recommended to keep this on, especially if the input references are imported from elsewhere rather than generated within CryoSPARC.

  • Number of extra final passes: Normally, refinement terminates when the gold standard FSC resolution stops improving. However, extra iterations can be forced by setting this parameter to the desired number of extra iterations.

  • Maximum align resolution (A): This can be set to limit the resolution of information used for alignment. By default, information up to the gold standard FSC resolution is used for alignment, but higher resolution information can be ignored by setting this parameter. This can occasionally help prevent the build up of high-frequency overfit noise.

  • Initial lowpass resolution (A): The resolution to which the initial reference is lowpass filtered can be controlled by setting this parameter to the desired resolution in Angstroms. For smaller molecules, it may help to decrease this value to around 20 Å.

  • GSFSC split resolution (A): The resolution to which each half-set is considered independent can be controlled by setting this parameter.

  • Minimize over per-particle scale: This enables estimation of per-particle scale factors during Expectation-Maximization. This can help if ice thicknesses varied greatly during data collection. The iteration at which per-particle scale estimation begins can be controlled by setting the Scale min/use start iter parameter to the desired iteration number.

  • B-Factor for plotting: This sets the b-factor used during map sharpening and plotting. Negative values sharpen the structure, and positive values blur the structure. By default, Guinier estimation determines the b-factor used at each iteration.

  • Computational minibatch size: This controls the number of images in each minibatch, which influences the amount of memory that needs to be allocated for each batch. If GPU memory is limited, the minibatch size can be decreased to prevent memory allocation errors; if there is ample GPU memory, this could be increased.

  • Mask (dynamic, static, none): This controls the type of masking to use. This can be set to the following options:

    • dynamic, in which case a dynamic mask will be generated based on the reference at each iteration according to the dynamic masking parameters below.

    • static, in which case an initial mask must be provided, and it will be used unmodified at each iteration.

    • none, in which case no mask will be used during the refinement.

  • Dynamic masking parameters:

    • Dynamic mask near (A): This controls the distance (away from the thresholded reference) at which the mask is dilated. At the near distance, the mask value is 1.0.

    • Dynamic mask far (A): This controls the distance (away from the thresholded reference) at which the mask is softly reduced to 0.0.

    • Dynamic mask start resolution (A): When the map reaches this resolution (in Angstroms), dynamic masking will start.

  • Cache particle images on SSD: Particle images can be copied to the SSD for much faster read times during refinement, which dramatically speeds up the job. If this is enabled, particle images will remain cached on the SSD for future jobs using the same particle stack and running on the same node.

Output

  • Refined 3D map

  • Half-maps

  • Mask used in refinement

  • Mask used in FSC calculation

  • Gold-standard FSC curve

  • Plots, including orientation distribution

Notes

Common Next Steps

  • Download and inspect map

For higher-order CTF aberration support, as well as faster codepaths and greater memory efficiency, refer to the job, which subsumes the features of this job.

Launch a job to sharpen the volume with different b-factors

Launch a job to generate templates from the reference, and iterate particle picking using the

Homogeneous Refinement
Homogeneous Refinement
Sharpening Tools
Create Templates
Template Picker