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python library for working with ontologies and ontology associations

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When fetching associations, say gene to phenotype associations, `AssociationSetFactory` populates an association map for each subject. But this code does not handle associations with multiple relations. For example, `HGNC:6764` has...

https://nbviewer.jupyter.org/github/biolink/ontobio/blob/master/notebooks/Phenotype_Enrichment.ipynb and binder: https://hub.gke.mybinder.org/user/biolink-ontobio-actww75g/notebooks/notebooks/Phenotype_Enrichment.ipynb The notebook creates but step 7 doesn't create an enrichment list: ![Screen Shot 2019-09-19 at 6 51 22 PM](https://user-images.githubusercontent.com/24249870/65293025-8cd05780-db0e-11e9-9d95-5a3345e181d7.png) I have tried locally and it's the...

Hi there, When using the Ontobio python library, a "keyerror" occured. (Was testing with the code maybe 5 days ago, it's working, but it suddenly breaks today). Here's the detailed...

The new Monarch beta API is not serving inferred phenotypes and added some EFO terms. The corresponding Monarch ticket is: https://github.com/monarch-initiative/dipper/issues/824 From Kent: "for HPO terms, there is some discussion...

Hi ! This PR (finally) adds a native OBO parser using the [`fastobo`](https://pypi.org/project/fastobo/) package. This is very much WIP since there are no actual semantics for OBO to OBO Graphs...

When https://github.com/biolink/ontobio/pull/346 was merged, the `create_ontology()` function in `ontol_factory.py` now has `ignore_cache=self.config.ignore_cache` being passed in. Other places in ontobio (`bin/validate.py`) we explicitly pass in `ignore_cache`. This causes two variables named...

Includes test as well. Motivated by need to only obtain orthologs called by PANTHER

Currently we convert obo to json using the java obographs library (via an owltools wrapper), which creates as odd dependency The overall goal is stop consuming obo, but in the...

I often end up making dataframes within python jupyter notebooks in order to plot ontology summary statistics data using seaborn etc. E.g. ``` bplot = sns.boxplot(x='prefix', y='parent_count', data=df2, width=0.5, palette="colorblind")...