Installation

OncoMark is built on the deep learning framework TensorFlow. It is important to install a suitable version of TensorFlow depending on your compute platform (CPU/GPU) and Python environment. The official TensorFlow installation guide provides detailed instructions.

❗ Use Python v3.11.0 and Tensorflow v2.18.0

Step 1: Install TensorFlow

Visit the TensorFlow installation guide to choose the appropriate version for your system.

Example: Install TensorFlow with GPU Support

For systems with NVIDIA GPUs and CUDA support:

# Install TensorFlow with GPU support
pip install tensorflow[and-cuda]

Example: Install TensorFlow for CPU-Only

For systems without GPUs:

# Install TensorFlow for CPU-only
pip install tensorflow

Step 2: Install OncoMark

After successfully installing TensorFlow, you can install OncoMark directly from PyPI:

# Install OncoMark from PyPI
pip install OncoMark

Alternatively, to install the latest version directly from the GitHub repository:

# Install OncoMark from GitHub
pip install git+https://github.com/SML-CompBio/OncoMark.git

Step 3: Verify Installation

To verify that OncoMark is installed correctly, run the following commands in Python:

import OncoMark
print(OncoMark.__version__)

If the command outputs the version number of OncoMark, the installation was successful.

Additional Requirements

Ensure that any dependencies, such as joblib or pandas, are also installed. These will typically be installed automatically with OncoMark, but you can manually install them if needed:

pip install joblib==1.4.2 pandas==2.2.3 scipy==1.14.1 numpy==2.0.2

You’re ready to start using OncoMark! Explore its features to analyze hallmark activity from transcriptomics data.

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