This repository contains an analysis of Galson 2015 and Galson 2016 vaccination studies from the Observed Antibody Space database (http://opig.stats.ox.ac.uk/webapps/oas/) and pipeline focusing on preprocessing and prediction of HepB specificity of antibodies.
The full data can be downloaded from the official webpage of Observed Antibody Space - http://opig.stats.ox.ac.uk/webapps/oas/downloads.
The Makefile (GNU Make) contains targets for data preprocessing, data analysis and models' training. The Makefile targets have been executed on a high-performance computing cluster. Therefore, in the targets, internal HPC library responsible for handling the jobs on the cluster is being used.
The bin folder contains python scripts responsible for data preprocessing and predictions as well as modules for visualizations and evaluations.
The bin/fairseq_plugins folder contains custom fairseq extensions such as the custom RoBERTa architecture that is used in this work.
The notebooks folder contains jupyter notebooks with data preprocessing, data analysis, as well as evaluations of the models and representation visualizations of the data.
Fully-trained baselines in a zip file and checkpoints of RoBERTa models are available in the models folder.
The text folder contains thesis in PDF format and the text/source folder contains its corresponding source files.
The setup.py serves for python module installation and environment.yml is a yaml file listing required conda dependencies.