CryoSPARC Guide
  • About CryoSPARC
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  • 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
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      • cryosparcm reference
      • cryosparcm cli reference
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    • 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
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      • Guide: Queuing Directly to a GPU
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      • 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
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  • 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
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        • Job: Import Result Group
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      • Motion Correction
        • Job: Patch Motion Correction
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        • 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
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        • Job: Ab-Initio Reconstruction
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        • Job: Homogeneous Refinement
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        • Job: Global CTF Refinement
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        • 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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On this page
  • Step 1 - Preprocess Data
  • Step 2 - Create Training Job
  • Step 3 - Create Topaz Extract Job
  • Step 4 - Acquire Particles from Topaz Extract
  • Next Steps
  1. Processing Data in cryoSPARC
  2. All Job Types in CryoSPARC
  3. Deep Picking
  4. Topaz (Bepler, et al)

T20S Proteasome: Topaz Particle Picking Tutorial

Topaz particle picking tutorial via the Topaz wrapper available in CryoSPARC.

PreviousTopaz (Bepler, et al)NextT20S Proteasome: Topaz Micrograph Denoising Tutorial

Last updated 2 years ago

Step 1 - Preprocess Data

  • Preprocess the T20S subset by completing steps 1-12 in the tutorial found in the Cryo-EM Data Processing in CryoSPARC: Introductory Tutorial section found here:

  • Ensure that the Inspect Picks, and Select 2D jobs from the linked tutorial are completed as they will be required for training the Topaz model. The ouputs from these two jobs will be used as inputs for the Topaz-related jobs.

Step 2 - Create Training Job

  • Select Topaz Train (BETA) from the Job Builder. Drag and drop the micrographs output from the completed Inspect Picks job and the particles_selected output from the completed Select 2D job into the micrographs and particles inputs respectively.

  • Use the file browser (activated by clicking the folder icon) to locate the Topaz executable path found in the Deep Picking section for the Path to Topaz Executable field. Instructions on how to find the Topaz executable path can be found above.

  • Modify the Downsampling factor parameter to 16. This parameter reduces the size of the input micrographs by the factor input and is often necessary to conform to a system's memory constraints.

  • Modify the Expected number of particles parameter to 300.

  • Queue the job.

  • The job is training a Topaz model on the subset of 20 micrographs from the T20S tutorial. It is highly recommended to train deep picker models on subsets of micrographs as acquiring training picks for all micrographs takes time and is not required. Once the Topaz model learns on a sufficient subset of the micrographs, it can pick particles from the entire dataset.

Step 3 - Create Topaz Extract Job

  • Select Topaz Extract (BETA) from the Job Builder. Drag and drop both the topaz_model and micrographs outputs from the Topaz Train job into the corresponding inputs on the Job Builder.

  • Use the file browser (activated by clicking the folder icon) to locate the Topaz executable path found earlier for the Path to Topaz Executable field.

  • Queue the job.

  • The job is using the trained Topaz model to infer picks from the input micrographs. Even though in this tutorial, the job is picking from the same micrographs used to train the model, a properly trained model will infer picks that were not used as training picks from the micrographs.

Step 4 - Acquire Particles from Topaz Extract

  • Select Extract from Micrographs from the Job Builder. Drag and drop both the micrographs and the particles outputs from the Topaz Extract job into the corresponding inputs on Job Builder.

  • Queue the job.

  • This job will update the particle picks with information required for further processing.

  • Select 2D Classification from the Job Builder. Drag and drop the particles output from the Extract from Micrographs job into the particles input of the 2D Classification job.

  • Queue the job.

  • Select Select 2D classes from the Job Builder. Drag and drop both outputs of the 2D Classification job into their corresponding inputs in the Select 2D classes job.

  • Queue the job.

  • Wait for the job status to change to "Waiting" and then select the particle templates that should be kept for further processing.

  • The 2D Classification and Select 2D classes jobs serve to filter out unwanted particles from the particle picking. Once the Select 2D classes job is complete, the particles output from the job can be used as particle picks to process further into the pipeline.

Next Steps

Now that a basic Topaz pipeline has been completed, the more advanced aspects of particle picking with Topaz can be explored. The following are some of these aspects:

  • Ideally, deep picking models are trained on a subset of micrographs and then perform inference on an entire dataset, as mentioned before. The Topaz model trained in this tutorial can be applied to the entire T20S dataset rather than the subset used in this tutorial. Potential refinement results will improve with the resultant increased number of picks.

  • The Topaz Train and Topaz Cross Validation jobs has many training parameters that can be fine tuned to affect the quality of the model.

Get Started with CryoSPARC: Introductory Tutorial (v3)
Passing inputs to the Topaz Train job
Passing inputs to the Topaz Extract job