KGO

Kowledge Graphs and Ontologies: code and data for the paper Transformation of Biomedical Data into Knowledge Graphs and Ontologies.

Zenodo DOI	Test Status	Coverage

Table of Contents

• KGO
  • Table of Contents
  • Summary
  • Usage
    • Setup
    • Execution
  • Citation

Summary

This project implements a method of transforming biomedical gene-phenotype data into knowledge graphs and corresponding ontologies. This is demonstrated with a single data -> script -> output workflow.

The project is laid out as follows:

• src/main_dystonia_graph_and_ontology_method.py: the main Python file running the experiment.
• data/: the data files necessary to run the experiment.
• out/: the destination for the generated files from the experiment.
• example_output/: example files demonstrating the output of the experiment.

Usage

This project contains a main Python script that processes biomedical gene-phenotype dystonia data and outputs graph files of various kinds. This follows the pattern of creating a virtual Python environment, installing dependencies, running the main file, and exploring the output files. Brief installation instructions can be found in Setup, and use of the scripts can be found in Execution.

Setup

Create and activate a virtual Python environment with your favorite tool (e.g., conda, mamba, or venv).

For example, with conda:

conda create -n kgo python=3.11
conda activate kgo

Next, install dependencies while inside this virtual environment via the requirements.txt file at the top of this repo:

pip install -r requirements.txt

Execution

The entire experiment lives in a file called src/main_dystonia_graph_and_ontology_method.py. To execute it, simply run the file through the Python interpreter while in your virtual environment as follows:

python src/main_dystonia_graph_and_ontology_method.py

Three files are generated and saved to the out/ directory. Examples of the files that should be generated can be seen in the example_output/ directory.

Citation

This project has a citation file file that generates citation information for the repository, which can be accessed at the "Cite this repository button" under the "About" section of the GitHub page.

The latest archival of the project is also at https://doi.org/10.5281/zenodo.10463050, which has its own tools for generating citations according to your favorite citation style.