Installation

XChrom is a deep learning project developed with TensorFlow 2.6.0 and Python 3.8, requiring GPU acceleration support. This documentation provides complete installation and configuration instructions.

If you haven’t installed conda yet, please download and install Miniconda or Anaconda first.

1. Create and Activate Conda Environment

# Create a Python 3.8 environment named XChrom
conda create -n XChrom python=3.8

# Activate the environment
conda activate XChrom

2. Install Git and Clone the Project

# Install Git
conda install git

# Clone the project
git clone https://github.com/Miaoyuanyuan777/XChrom.git

3. Install TensorFlow GPU Version

Two installation methods are available:

  1. Install with conda

conda install tensorflow-gpu=2.6.0 -c conda-forge

  1. Install with pip

pip install tensorflow-gpu==2.6.0

4. Install CUDA and cuDNN

# Install CUDA 11.2 and cuDNN 8.1
conda install cudatoolkit=11.2 cudnn=8.1 -c conda-forge

After installation, run the following command to verify that TensorFlow can correctly recognize the GPU:

python -c "import tensorflow as tf; print(tf.__version__); print(tf.config.list_physical_devices('GPU'))"

If the output shows TensorFlow version 2.6.0 and detects GPU devices, the installation was successful.

5. Install Project Dependencies

cd XChrom/

# Install all dependencies listed in requirements.txt
pip install -r requirements.txt

# Install XChrom
pip install .

Requirements of XChrom

anndata==0.9.2
biopython==1.79
ConfigArgParse==1.7
logomaker
matplotlib==3.5.1
pandas==1.4.1
pysam==0.23.3
scanpy==1.9.5
scikit-learn==1.0.2
scipy==1.8.0
setuptools
tqdm
tensorflow-gpu==2.6.0
protobuf==3.20.3
numpy
h5py==3.1.0
typing_extensions==3.7.4.3
keras==2.6.0