TCRembedding is a composite of multiple methods for embedding amino acid sequences. Read the full documentation here.
Since different methods rely on different runtime environments and there may be version conflicts between the dependent packages, we suggest that you create a virtual environment to use the embedding methods. At the same time, we provide an installation script env_creator.py, the script will be based on different embedding methods, create the corresponding virtual environment. The following is an example of how to use it:
(recommended) Based on Linux , python 3.8.
python env_creator.py <base_dir> <env_name> [--mirror_url=<url>]
base_dir : The base directory where virtual environments will be created.You also need to make sure that the corresponding requirements.txt file is in this directory.The requirements.txt file for each embedding method is available under src/TCRembedding/method_name/.
env_name : The name of the virtual environment.
mirror_url : The mirror URL for pip installations.
Example:
python env_creator.py /media/lihe/TCR/Word2Vec Word2vec --mirror_url=https://pypi.tuna.tsinghua.edu.cn/simple
The command to activate the virtual environment is printed at the end of the script run and the user can run the virtual environment according to the instructions.
Example:
source /media/lihe/TCR/Word2Vec/Word2vec/Word2vec_venv/bin/activate
After entering the virtual environment, use the pip command to install TCRembedding.
pip install tcrembedding
In addition to running the env_creator.py script to create virtual environments, you can also create and manage virtual environments via conda.
Example:
conda create --name word2vec python=3.8
conda activate word2vec
pip install -r src/TCRembedding/Word2Vec/requirements.txt
pip install tcrembedding
Note:
If you encounter an issue during installation with the message "cannot import name 'msvccompiler' from 'distutils'," please first ensure that the setuptools version is below 65.0.0 or use version 65.0.2. Additionally, add the --no-build-isolation parameter when using the pip command.
If you use TCREmbedding in your work, please cite the TCREmbedding publication as follows:
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