We introduce BioDataFuse, a query-based Python tool for seamless integration of biomedical databases. BioDataFuse establishes a modular framework for efficient data wrangling, enabling context-specific knowledge graph creation and supporting graph-based analyses. With a user-friendly interface, it enables users to dynamically create knowledge graphs from their input data. Supported by a robust Python package, pyBiodatafuse, this tool excels in data harmonization, aggregating diverse sources through modular queries. Moreover, BioDataFuse provides plugin capabilities for Cytoscape and Neo4j, allowing local graph hosting. Ongoing refinements enhance the graph utility through tasks like link prediction, making BioDataFuse a versatile solution for efficient and effective biological data integration.
The most recent release can be installed from PyPI with:
$ pip install pyBiodatafuseThe most recent code and data can be installed directly from GitHub with:
$ pip install git+https://github.com/BioDataFuse/pyBiodatafuse.gitContributions, whether filing an issue, making a pull request, or forking, are appreciated. See CONTRIBUTING.md for more information on getting involved.
The code in this package is licensed under the MIT License.
The work was started as part of the Elixir BioHackathon 2023 integrating and bringing together multiple Core Data Resources together.
Gadiya, Y., Ammar, A., Willighagen, E., Martinat, D., Sima, A. C., Balci, H., & Abbassi Daloii, T. (2023). BioHackEU23 report: Extending interoperability of experimental data using modular queries across biomedical resources. BioHackrXiv Preprints. https://doi.org/10.37044/osf.io/mhsqp
This package was created with @audreyfeldroy's cookiecutter package using @cthoyt's cookiecutter-snekpack template.
See developer instructions
The final section of the README is for if you want to get involved by making a code contribution.
To install in development mode, use the following:
$ git clone git+https://github.com/BioDataFuse/pyBiodatafuse.git
$ cd pyBiodatafuse
$ pip install -e .After cloning the repository and installing tox with pip install tox, the unit tests in the tests/ folder can be
run reproducibly with:
$ toxAdditionally, these tests are automatically re-run with each commit in a GitHub Action.
The documentation can be built locally using the following:
$ git clone git+https://github.com/BioDataFuse/pyBiodatafuse.git
$ cd pyBiodatafuse
$ tox -e docs
$ open docs/build/html/index.htmlThe documentation automatically installs the package as well as the docs
extra specified in the setup.cfg. sphinx plugins
like texext can be added there. Additionally, they need to be added to the
extensions list in docs/source/conf.py.
After installing the package in development mode and installing
tox with pip install tox, the commands for making a new release are contained within the finish environment
in tox.ini. Run the following from the shell:
$ tox -e finishThis script does the following:
- Uses Bump2Version to switch the version number in the
setup.cfg,src/pyBiodatafuse/version.py, anddocs/source/conf.pyto not have the-devsuffix - Packages the code in both a tar archive and a wheel using
build - Uploads to PyPI using
twine. Be sure to have a.pypircfile configured to avoid the need for manual input at this step - Push to GitHub. You'll need to make a release going with the commit where the version was bumped.
- Bump the version to the next patch. If you made big changes and want to bump the version by minor, you can
use
tox -e bumpversion -- minorafter.