This PR adds a setup.py file to the BigMHC repo, which allows users to install BigMHC using pip on the command line. The README.md has been updated with the new installation instructions. Please note, that these still point to the griffithlab fork of the repo so if the PR is accepted, the pip install command needs to be further updated to point to the KarchinLab version of the repository.
The setup.py defines two scripts: src/bigmhc_predict' and 'src/bigmhc_train. When BigMHC is installed with pip, this results in users being able to run the prediction and training via command line commands bigmhc_predict and bigmhc_train instead of the previous predict.py and train.py. The advantage of this approach is that these command line commands are location-agnostic and no longer need to be executed from within the src directory.
The setup.py also defines all required dependency, which will automatically be installed when the pip install command is run. Manual installation of these dependency are no longer required.
This PR adds a setup.py file to the BigMHC repo, which allows users to install BigMHC using pip on the command line. The README.md has been updated with the new installation instructions. Please note, that these still point to the griffithlab fork of the repo so if the PR is accepted, the pip install command needs to be further updated to point to the KarchinLab version of the repository.
The setup.py defines two scripts:
src/bigmhc_predict' and 'src/bigmhc_train. When BigMHC is installed with pip, this results in users being able to run the prediction and training via command line commandsbigmhc_predictandbigmhc_traininstead of the previouspredict.pyandtrain.py. The advantage of this approach is that these command line commands are location-agnostic and no longer need to be executed from within the src directory.The setup.py also defines all required dependency, which will automatically be installed when the pip install command is run. Manual installation of these dependency are no longer required.