A package for generating curation sheets for rationally enriching a BEL graph using INDRA and PyBEL.
Project description
A package for generating curation sheets for rationally enriching a BEL graph.
If you find bel_enrichment useful in your work, please consider citing [1]:
Additionally, this package also heavily builds on INDRA [2] and PyBEL [3].
Installation
bel_enrichment can be installed from PyPI with the following command:
$ pip install bel_enrichment
The latest version can be installed from GitHub with:
$ pip install git+https://github.com/bel-enrichment/bel-enrichment.git
You’ll need to set the INDRA_DB_REST_URL and INDRA_DB_REST_API_KEY in the ~/.config/indra/config.ini file. Please contact the INDRA team for credentials.
Rational Enrichment
Generate a folder full of curation sheets based on the given BEL graph that has been pre-compiled by PyBEL. Use --info-cutoff to specify the minimum information density cutoff. 1.0 means that the node has no edges, .5 means one edge, and so on. Use --belief-cutoff to specify the minimum belief score from INDRA for adding the statement to the sheet. Higher belief means the more chance a statement is already right.
$ bel-enrichment from-graph zhang2011.bel --directory ~/Desktop/zhang-enrichment
Generate a ranking for genes based on the information content in a given BEL graph that has been pre-compiled by PyBEL.
$ bel-enrichment ranks zhang2011.bel
Document-Based Curation
If you want to make a curation sheet based on a PubMed identifier (or list of them) do this:
$ bel-enrichment from-pmids 20585587 20585588 > ~/Desktop/document_based.tsv
Topic-Based Curation
If you want to make a curation sheet based on an entity, do this:
$ bel-enrichment from-agents MAPT GSK3B > ~/Desktop/topic_based.tsv
References
Gyori, B. M., et al. (2017). From word models to executable models of signaling networks using automated assembly. Molecular Systems Biology, 13(11), 954.
Hoyt, C. T., Konotopez, A., Ebeling, C., (2017). PyBEL: a computational framework for Biological Expression Language. Bioinformatics (Oxford, England), 34(4), 703–704.
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