This application will derive characteristic and discriminatory explanations for groups of entities described by ontology classes. For example, groups of patients described by HPO classes. For more information, please read the paper (now accepted!).
Here is the most recent stable release. To install, you just have to extract either the ZIP or Tar file, then either run the klarigi binary from the extracted folder directly, or add it to your PATH (see the later linked tutorial for an example). You can also check out the snapshot release, which includes lots of performance improvements and some bug fixes.
This tutorial will walk you through how to use Klarigi. You can also run klarigi -h to see a full list of options and parameters.
- Papers:
- Klarigi: Characteristic Explanations for Semantic Data
- This paper describes the algorithms and thinking in-depth, with much discussion and application to two use cases.
- Multi-faceted Semantic Clustering With Text-derived Phenotypes
- This describes some of the very early thoughts behind the algorithm, but doesn't represent the current state.
- Klarigi: Characteristic Explanations for Semantic Data