WormLib

BASICS:

  • Installation
  • Input
  • Configuration (YAML Settings)
  • Output Files and Results Structure
  • Pre-Trained Models
WormLib
  • WormLib documentation
  • View page source

WormLib documentation

WormLib is a modular open-source image analysis library for quantifying microscopy images of Caenorhabditis elegans embryos. It provides an end-to-end pipeline from image loading, embryo segmentation, cell identity prediction, single-molecule FISH (smFISH) spot detection, and spatial mRNA analysis.

BASICS:

  • Installation
    • Quick Install with Conda
    • Core Dependencies
    • Troubleshooting
    • Next Steps
  • Input
    • Supported Image Formats
    • File Organization Best Practice
    • Loading Images in Code
  • Configuration (YAML Settings)
    • Configuration Structure
    • Input Section
    • Microscope Section
    • Channels Section
    • Segmentation Section
    • Pipeline Section
    • Example Configs
    • Using Configuration Files
    • Next Steps
  • Output Files and Results Structure
    • Output Directory Structure
    • Visualization Outputs (PNG)
    • Quantification Outputs (CSV)
    • PDF Report
    • Interpreting Results
    • Troubleshooting Output Issues
    • Next Steps
  • Pre-Trained Models
    • Cell Classification Models (Random Forest)
    • Cellpose Segmentation Model
    • Using Models in Code
    • Disabling Classification
    • Model Limitations and Best Practices
    • Training Custom Models
    • Citation
    • Next Steps
Next

© Copyright 2026, Naly Torres, Luis de Lira Aguilera, Karissa Coleman, Richard Bruno, Brian Munsky, Erin Osborne Nishimura.

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