A package for converting KEGG gene sets into BEL


Keywords
Biological, Expression, Language, BEL, Systems, Biology, KEGG, biological-expression-language, networks-biology, pathways, proteins, systems-biology
License
MIT
Install
pip install bio2bel-kegg==0.3.0

Documentation

Bio2BEL KEGG Build Status Coverage Status Documentation Status zenodo

This package allows the enrichment of BEL networks with KEGG information by wrapping its RESTful API. Furthermore, it is integrated in the ComPath environment for pathway database comparison.

If you find this package useful, please consider citing [domingofernandez2018]:

[domingofernandez2018] Domingo-Fernandez, D., et al (2018). ComPath: an ecosystem for exploring, analyzing, and curating mappings across pathway databases. Npj Systems Biology and Applications, __5__(1), 3.

Warning This package creates partOf relationships in BEL, but does not convert KEGG mechanistic relationships to BEL. That functionality is implemented in the PathMe project.

Installation Current version on PyPI Stable Supported Python Versions MIT License

bio2bel_kegg can be installed easily from PyPI with the following code in your favorite terminal:

$ pip install bio2bel_kegg

or from the latest code on GitHub in development mode with:

$ git clone https://github.com/bio2bel/kegg.git
$ cd kegg
$ pip install -e .

Setup

KEGG can be downloaded and populated from either the Python REPL or the automatically installed command line utility.

Python REPL

>>> import bio2bel_kegg
>>> kegg_manager = bio2bel_kegg.Manager()
>>> kegg_manager.populate()

Command Line Utility

bio2bel_kegg populate

Other Command Line Utilities

  • Run an admin site for simple querying and exploration python3 -m bio2bel_kegg web (http://localhost:5000/admin/)
  • Export gene sets for programmatic use python3 -m bio2bel_kegg export

Citation

  • Kanehisa, Furumichi, M., Tanabe, M., Sato, Y., and Morishima, K.; KEGG: new perspectives on genomes, pathways, diseases and drugs. Nucleic Acids Res. 45, D353-D361 (2017).
  • Kanehisa, M., Sato, Y., Kawashima, M., Furumichi, M., and Tanabe, M.; KEGG as a reference resource for gene and protein annotation. Nucleic Acids Res. 44, D457-D462 (2016).
  • Kanehisa, M. and Goto, S.; KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 28, 27-30 (2000).