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3. STAR

The partinet star command is the final step in your particle picking pipeline. It converts the particle coordinates detected in the previous stage into a standardized STAR file format that can be used with downstream cryo-EM processing software like RELION, cryoSPARC, or other reconstruction programs.

Quick Start​

Local Installation
partinet star \
    --labels /data/partinet_picking/exp/labels \
    --images /data/partinet_picking/denoised \
    --output /data/partinet_picking/output.star \
    --conf 0.1
Apptainer/Singularity
apptainer exec --nv --no-home \
    -B /data oras://ghcr.io/wehi-researchcomputing/partinet:main-singularity partinet star \
    --labels /data/partinet_picking/exp/labels \
    --images /data/partinet_picking/denoised \
    --output /data/partinet_picking/output.star \
    --conf 0.1
Docker
docker run --gpus all -v /data:/data \
    ghcr.io/wehi-researchcomputing/partinet:main partinet star \
    --labels /data/partinet_picking/exp/labels \
    --images /data/partinet_picking/denoised \
    --output /data/partinet_picking/output.star \
    --conf 0.1

Parameters​

ParameterTypeRequiredDescription
--labelsPathYesDirectory containing the particle coordinate files (.txt format) from the detection stage
--imagesPathYesDirectory containing the denoised micrographs corresponding to the labels
--outputPathYesOutput path for the generated STAR file
--confFloatYesConfidence threshold for filtering particle coordinates (0.0-1.0)

Input Requirements​

At this stage of the pipeline, your directory structure should look like:

partinet_picking/
├── motion_corrected/          # 📁 Your input micrographs
│   ├── micrograph1.mrc
│   ├── micrograph2.mrc
│   └── ...
├── denoised/                  # 🧹 Created by denoise stage
│   ├── micrograph1.mrc
│   ├── micrograph2.mrc
│   └── ...
├── exp/                       # 🎯 Created by detect stage
│   ├── labels/               # 📋 Detection coordinates
│   │   ├── micrograph1.txt
│   │   ├── micrograph2.txt
│   │   └── ...
│   ├── micrograph1.mrc       # 🖼️ Micrographs with detections drawn
│   ├── micrograph2.mrc
│   └── ...
└── partinet_detect.log
└── partinet_denoise.log

Confidence Threshold​

The --conf parameter controls the quality filtering of detected particles:

  • Typical range: 0.1-0.3 for most datasets

Choose your confidence threshold based on:

  • Dataset quality and signal-to-noise ratio
  • Downstream processing requirements
  • Balance between particle quantity and quality

CryoSPARC Output​

The command generates a STAR file compatible with CryoSPARC containing:

  • Particle coordinates (X, Y positions)
  • Corresponding micrograph paths

RELION output​

Use --relion and --relion-project-dir to generate RELION-compatible STAR outputs under <relion_project>/partinet:

  • Micrograph manifest: <relion_project>/partinet/pick.star
  • Per-micrograph coordinates: <relion_project>/partinet/movies/<micrograph_basename>.star

Example:

partinet star \
  --labels /data/partinet_picking/exp/labels \
  --images /data/partinet_picking/denoised \
  --output /data/partinet_picking/output.star \
  --conf 0.2 \
  --relion \
  --relion-project-dir /data/relion/EMPIAR-10089 \
  --mrc-prefix MotionCorr/job003/movies

Next Steps​

After generating your STAR file, you can:

  • Import it into RELION/CryoSPARC for 2D classification and 3D reconstruction
  • Perform additional particle filtering or sorting based on your specific needs
warning

If you are using PartiNet v1.0.0, the Denoise flips micrographs in the y-axis due to matrix transpose operations. If you denoised micrographs in PartiNet ensure that when you import and extract particle coordinates that you toggle Flip in y in CryoSPARC prior to particle extraction. This has been fixed in v1.0.1+. You can check your version with partinet --help