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MERSCOPE Visualizer ↔ Python Tutorial

A round-trip workflow between the MERSCOPE Visualizer and Python spatial-omics tools, demonstrated on a breast tissue microarray (TMA) dataset.

What it does

  1. Load raw MERSCOPE output into an AnnData object (scanpy)
  2. Subset to cells manually selected in the Visualizer (selected.csv)
  3. Run BANKSY neighborhood clustering on the subset
  4. Export cluster labels back to selected.csv format for re-loading in the Visualizer

Usage

# One-time setup (run from repo root)
uv sync
.venv/bin/python -m ipykernel install --user --name merscope-banksy --display-name "merscope-banksy"

Open merscope_banksy_tutorial.ipynb, select the merscope-banksy kernel, and run all cells.