cellColor 0.1.3

An app for exploring spatial transcriptomics and cell segmentations by overlaying data

Gene Visualization Tool (cellColor)

An interactive desktop application for visualizing spatial transcriptomics data, cell segmentation masks, and microscopy images.
Perfect for verifying cell segmentation accuracy and exploring spatial gene expression patterns.

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👥 Credits & Project Team

• Developer: Anthea Guo
• Mentor: Kushal Nimkar
• Principal Investigator (PI): Prof. Karthik Shekhar

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✨ Features

• Image Loading & Zooming:
  Load tissue/microscopy images, zoom into regions, and reset to full view.

• Cellpose Segmentation Overlay:
  Overlay Cellpose-generated segmentation masks or outlines with smooth, cached zooming.

• Transcript Visualization:
  Import transcript coordinates (x, y, gene), align with images using transformation matrices, and overlay selected genes.

• Single-Cell Integration:
  Load AnnData cell center positions (.h5ad), toggle display, and customize appearance.

• User-Friendly Toolbar:
  Intuitive controls for overlays and zoom, live status feedback, and collapsible navigation frames.

• Data Alignment:
  Load transformation matrices for accurate transcript-image alignment.

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🚀 Installation

Option 1: Local Development (Editable Mode)

git clone https://github.com/crocodile27/cellColor.git
cd cellColor
conda create -n cellcolor python=3.10
conda activate cellcolor
pip install -e .

Run locally:

cellColor

Option 2: Install via PyPI (v0.1.0)

pip install cellColor

Release: September 1, 2025 (PyPI link)

Launch:

cellColor

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📂 Supported Data Formats

• Images: .png, .jpg, .tif, etc.
• Cellpose Masks: .npy arrays or image masks.
• Detected Transcripts: CSV/TSV with x, y, gene columns.
• Transformation Matrix: CSV/TSV for alignment.
• AnnData: .h5ad with cell coordinates.

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🧪 Example Workflow

1. Open the app: cellColor
2. Load image:
   File → Load Image to display tissue section.
3. Load transcripts & matrix:
   File → Load Detected Transcripts and Transformation Matrix.
4. Load Cellpose masks:
   File → Load Cellpose Masks, then enable Show Cellpose Masks.
5. Overlay gene transcripts:
   Select a gene from the dropdown to view transcript spots.
6. (Optional) Load cell centers:
   File → Load AnnData Cell Centers, enable Show Cell Centers.
7. Zoom & reset:
   Zoom into areas of interest; use Reset Zoom to return.