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Get Started

This page walks you through launching UELer for the first time.

Prerequisites

Make sure you have completed installation before proceeding.

1. Open the Notebook

  1. Activate your environment:

    micromamba activate ark-analysis-ueler

  2. Open your notebook environment (JupyterLab, Jupyter Notebook, or VS Code).

  3. Navigate to the cloned UELer repository and open:

    script/run_ueler.ipynb

  4. Select the ark-analysis-ueler kernel for the notebook.

2. Configure Your Data Paths

The notebook requires you to set a few paths at the top. Edit the configuration cell:

base_folder = "/path/to/your/image_data"          # Required
masks_folder = "/path/to/segmentation/output"     # Optional
annotations_folder = "/path/to/annotations"        # Optional
cell_table_path = "/path/to/cell_table.csv"       # Optional
Variable Description Required
base_folder Directory containing the FOV folders with channel images ✅ Yes
masks_folder Directory containing segmentation .tif files ❌ Optional
annotations_folder Directory containing annotation raster .tif files ❌ Optional
cell_table_path Path to the CSV cell table ❌ Optional

Minimal setup

You can run UELer with only base_folder set. Masks, annotations, and the cell table are all optional — the viewer will simply skip those features when the paths are not provided.

3. Run the Notebook

Run all cells in run_ueler.ipynb. The viewer will appear inline in the notebook output.

4. Expected Folder Structure

UELer expects your image data to follow this layout:

base_folder/
├── fov1/
│   ├── CD3.tiff
│   ├── CD8.tiff
│   └── DAPI.tiff
├── fov2/
│   ├── CD3.tiff
│   └── ...
└── ...

Each subdirectory is treated as one FOV (Field of View). Channel files must be single-channel TIFF images named by the channel/marker.

5. Try It on Binder

No local setup? Try UELer directly in your browser:

Binder

Next Steps