https://github.com/cthoyt/twin-identifier-analysis

How many local unique identifiers overlap between each biomedical vocabulary in the Bioregistry?
https://github.com/cthoyt/twin-identifier-analysis

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How many local unique identifiers overlap between each biomedical vocabulary in the Bioregistry?

• Host: GitHub
• URL: https://github.com/cthoyt/twin-identifier-analysis
• Owner: cthoyt
• License: mit
• Created: 2023-02-10T11:40:01.000Z (almost 2 years ago)
• Default Branch: main
• Last Pushed: 2023-02-13T18:24:15.000Z (over 1 year ago)
• Last Synced: 2024-06-12T02:34:46.908Z (5 months ago)
• Language: Jupyter Notebook
• Size: 401 KB
• Stars: 2
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# twin-identifier-analysis

How many local unique identifiers overlap between each biomedical vocabulary in the Bioregistry?

This analysis is inside the [Jupyter notebook](twin-identifier-analysis.ipynb) in this repository. Note that running

this notebook requires quite a bit of setup for [`pyobo`](https://github.com/pyobo/pyobo) and caching of data, so I

haven't carefully added installation/reproduction instructions.

**Results**: There are a bit more than 300 resources in the Bioregistry that can be parsed with PyOBO. 134 of those were

parsable and had more than 10 identifiers. Almost all of them have meaningful overlap with at least one other

resource.

**Take-away message**: Using prefixes is vital to disambiguate between different namespaces. Endpoints like the neXtProt

term endpoint (as discussed in https://github.com/biopragmatics/bioregistry/issues/721) could have collisions between

local unique identifiers from resources like MeSH and NCIT.

Outputs:

- [graph.graphml](graph.graphml) - A generic graph format

- [graph.cytoscape.json](graph.cytoscape.json) - A JSON format compatible with Cytoscape

- [nodes.tsv](nodes.tsv) and [edges.tsv](edges.tsv) - Generic tab-separated values files describing the contents of the

  graph