Installation

HRCHY-CytoCommunity is available for Python 3.10. It does yet not support Apple silicon.

Hardware requirement

  • Memory: 2GB or more

  • Storage: 4GB or more

  • CUDA memory: 4GB or more (For CODEX example dataset K=50, #Cell=80000)

Software requirement

For convenience, we suggest using a separate conda environment for running HRCHY-CytoCommunity

Step 1. create conda environment

#create an environment called hrchy_cytocommunity_env
conda create -n hrchy_cytocommunity_env python=3.10

#activate your environment
conda activate hrchy_cytocommunity_env

Step 2. install additional libraries

To use HRCHY-CytoCommunity, you need to install some external libraries. These include:

  • PyTorch

  • PyG

  • scanpy

  • pandas

  • scipy

  • statsmodels

  • scikit-learn

  • seaborn

  • matplotlib

  • tqdm

PyTorch and PyG

We recommend to install the PyTorch libraries with GPU support. If you have CUDA, this can be done as:

pip install torch==${TORCH}+${CUDA} --index-url https://download.pytorch.org/whl/${CUDA}

where ${TORCH} and ${CUDA} should be replaced by the specific PyTorch and CUDA versions, respectively.

For example, for PyTorch 2.4.0 and CUDA 11.8, type:

pip install torch==2.4.0 --index-url https://download.pytorch.org/whl/cu118
pip install torch_geometric

Or using conda to install:

conda install pytorch==2.4.0  cudatoolkit=11.8
pip install torch_geometric

Other dependencies

then we install other library for anlysis

pip install scanpy pandas scipy statsmodels scikit-learn seaborn tqdm matplotlib

Alternative

Alternatively, we have provided a conda environment file with all required external libraries, which you can use as:

conda env create -f environment.yaml

Installation via PyPi

Subsequently, install HRCHY-CytoCommunity via pip:

pip install hrchy-cytocommunity