This repository contains the code for the UCS method, a unified approach to cell segmentation for spatially resolved transcriptomics. UCS is a deep learning-based method that can be used to segment cells in spatially resolved transcriptomics data. UCS can be used to segment cells in spatially resolved transcriptomics data from different platforms.

To prepare the environment:

cd /path/to/ucs
conda create -n ucs python=3.9
conda activate ucs
pip install -r requirements.txt

Then you can run the UCS method on your data. See scrips dir for examples on how to run UCS on Xenium data and Vizgen data.

See downstream dir README for examples on how to run downstream analysis to reproduce most of the results in the paper.