Installation

Important software Dependencies

• scanpy==1.9.3

• squidpy==1.3.0

• pytorch==1.13.1 (cuda==11.7)

• DGL==1.1.1 (cuda==11.7)

• R==4.2.0

• mclust==5.4.10

Note: The evaluation device for all the results in the article is an RTX3090.

Setup by Docker (Recommended)

1. Download the stCluster image from DockerHub and set up a container:

   docker run --gpus all --name your_container_name -idt hannshu/stcluster:latest
   

2. Access the container:

   docker start your_container_name
   docker exec -it your_container_name /bin/bash
   

3. Write a Python script to run stCluster. The anaconda environment for stCluster will be automatically activated in the container. The stCluster source code is located at /root/stCluster. Make sure to run git pull to update the code before using it.

Note: Ensure that nvidia-docker2 is properly installed on your host device. If not, follow the instructions to set up nvidia-docker2 first.

Setup by Anaconda

1. Install Anaconda.

2. Clone the stCluster repository from GitHub:

   git clone https://github.com/hannshu/stCluster.git
   

3. Download the dataset repository:

   git submodule init
   git submodule update
   

4. Import the conda environment:

   conda env create -f environment.yml
   

5. Write a Python script to run stCluster.