DeepBCR Project
If you used this software in your work, please cite:
DeepBCR: Deep learning framework for cancer-type classification and binding affinity estimation using B cell receptor repertoires
Authors: Xihao Hu, X Shirley Liu
Address: Department of Data Sciences, Dana-Farber Cancer Institute and Harvard T.H. Chan School of Public Health, Boston, MA, USA
Software Versions
- Python 3.6 (https://www.python.org/downloads/release/python-365/)
- TensorFlow 1.5.0 (https://www.tensorflow.org/install/)
- Numpy 1.14.3 (https://docs.scipy.org/doc/numpy-1.14.0/reference/)
- Pandas 0.21.0 (https://pandas.pydata.org/)
Setup the Environment
Install conda for python 2.7 (https://conda.io/docs/user-guide/install/download.html)
Create an empty environment in python 3.6
conda create -n py36 python=3.6
Load the environment and install required packages
source activate py36
conda install -y numpy pandas scikit-learn ipython tensorflow matplotlib seaborn jupyter
Test the Functions
Test all the deep learning models using a synthetic data
cd src/
python deep_bcr.py