MOSAIK

This pipeline transforms raw imaging and transcript data into cell-level expression profiles linked to cellular geometry, forming the core of spatial single-cell analysis. It covers the entire workflow, from loading the image to updating its SpatialData Zarr file with the newly generated segmentation data. The pipeline leverages the Cellpose-SAM Python library for cell segmentation.

Getting Started

• Introduction
• Workflow
• Software
• SpatialData Object
  • Core Concepts
  • Categories
  • Transformations
  • Visualization

Data Visualization

• CosMx Strategy
• Xenium Strategy
• How to use Napari
  • Install
  • Install CosMx plugin
  • Run stitching
  • Restart Napari
  • Explore

Data Integration

• Tools
• Extracting Files
• Initialization
  • CosMx Integration
  • Xenium Integration

Resegmentation

• Quick Start
• Installation
  • Prerequisites
  • Install Core Dependencies
  • Optional GPU Support
• Preprocessing
• Segmentation
• Post-Segmentation
  • Masks
  • Polygons
  • Labels
  • Coordinate Transformation
  • Advanced Filtering Examples
  • Understanding Filter Statistics
  • Performance Notes
• Outputs
  • Cell x Gene Matrix
  • Update SpatialData
• Usage Examples
  • Using the Resegmentation Class (reseg.py)
  • Using Individual Functions (reseg_tools.py)
  • Full Pipeline with Stitching and QC (reseg_script.py)
• API Reference
  • GPU Utilities
  • Image Preprocessing
  • Segmentation
  • Masks & Shapes
  • Labels
  • Points & Tables
  • Save Zarr File

Reference

• Citation
• Change Log
  • Version 1.0.0
• Contributions
  • 🛠️ How to Contribute