Installation

We recommend using Anaconda/Miniconda to create a conda environment for using CellDISECT.

1. Create and activate a conda environment:

conda create -n CellDISECT python=3.9
conda activate CellDISECT

2. Install PyTorch (tested with pytorch 2.1.2 and cuda 12):

conda install pytorch==2.1.2 torchvision==0.16.2 torchaudio==2.1.2 pytorch-cuda=12.1 -c pytorch -c nvidia

3. Install CellDISECT:

You can install the stable version using pip:

pip install celldisect

Install the beta version with Google Colab and newer dependency support:

pip install celldisect==0.2.0b1

Or install the latest development version from GitHub:

pip install git+https://github.com/Lotfollahi-lab/CellDISECT

Or install from local directory by cloning the repository for development:

git clone https://github.com/Lotfollahi-lab/CellDISECT.git
cd CellDISECT
pip install -e .

Optional Dependencies

For RAPIDS/rapids-singlecell support:

pip install \
    --extra-index-url=https://pypi.nvidia.com \
    cudf-cu12==24.4.* dask-cudf-cu12==24.4.* cuml-cu12==24.4.* \
    cugraph-cu12==24.4.* cuspatial-cu12==24.4.* cuproj-cu12==24.4.* \
    cuxfilter-cu12==24.4.* cucim-cu12==24.4.* pylibraft-cu12==24.4.* \
    raft-dask-cu12==24.4.* cuvs-cu12==24.4.*

pip install rapids-singlecell

For CUDA-enabled JAX:

pip install -U "jax[cuda12_pip]" -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html

Dependencies

CellDISECT has the following main dependencies:

  • anndata (>=0.10.8, <0.10.9)

  • scvi-tools (>=0.20.3, <1.0.0)

  • torch (>=2.1.0, <2.3.0)

  • scanpy

  • numpy (>=1.26.3, <1.27.0)

  • jax (>=0.4.16, <0.4.24)

  • lightning (>=2.2.0, <2.3.0)

For a complete list of dependencies, please refer to the pyproject.toml file in the repository.