Installation Guide

This guide will walk you through the process of installing SDEvelo and its dependencies.

System Requirements

Before installing SDEvelo, ensure your system meets the following requirements:

  • Operating Systems: Linux (Ubuntu, CentOS), macOS, Windows 10

  • Python Version: Python 3.8 and above

  • RAM: Minimum 8GB, 16GB or more recommended for larger datasets

  • Storage: At least 1GB of free disk space

Dependencies

SDEvelo requires the following Python packages:

  • anndata==0.10.7

  • matplotlib==3.7.1

  • numpy==1.23.5

  • scipy==1.8.1

  • scvelo==0.2.5

  • seaborn==0.11.2

  • torch==1.13.1+cu117

These will be automatically installed when you install SDEvelo.

Installation Steps

1. Set Up Python Environment

We recommend using a virtual environment to avoid conflicts with other Python packages. You can create one using venv or conda:

Using venv:

python3 -m venv sdevelo_env
source sdevelo_env/bin/activate  # On Windows, use `sdevelo_env\Scripts\activate`

Using conda:

conda create -n sdevelo_env python=3.8
conda activate sdevelo_env

2. Install SDEvelo

Once your environment is set up and activated, you can install SDEvelo using pip:

pip install sdevelo

This command will install SDEvelo and all its dependencies.

3. Verify Installation

To verify that SDEvelo has been installed correctly, you can run:

python -c "import sdevelo; print(sdevelo.__version__)"

This should print the version number of SDEvelo without any errors.

Installing from Source

If you want to install the latest development version of SDEvelo, you can install it directly from the GitHub repository:

pip install git+https://github.com/Liao-Xu/SDEvelo.git

GPU Support

SDEvelo can leverage GPU acceleration for faster computations. If you have a CUDA-capable GPU, ensure you have the appropriate CUDA toolkit installed. The PyTorch version installed with SDEvelo (1.13.1+cu117) is compatible with CUDA 11.7.

To check if PyTorch can access your GPU, run:

import torch
print(torch.cuda.is_available())

This should return True if your GPU is properly set up.

Troubleshooting

If you encounter any issues during installation:

  1. Ensure you’re using a supported Python version (3.8+).

  2. Check that you have the latest version of pip: pip install –upgrade pip

  3. If you’re having issues with PyTorch, you may need to install it separately following the instructions on the PyTorch website.

  4. Make sure you have sufficient permissions to install packages on your system.

For any persistent issues, please refer to our GitHub issues page or contact our support team.