{ "info": { "author": "Jeremy McRae", "author_email": "jeremy.mcrae@sanger.ac.uk", "bugtrack_url": null, "classifiers": [ "Development Status :: 3 - Alpha", "License :: OSI Approved :: MIT License" ], "description": "[![Build Status](https://travis-ci.org/jeremymcrae/hpo_similarity.svg?branch=master)](https://travis-ci.org/jeremymcrae/hpo_similarity)\n\n#### Similarity of phenotypes in patient groups\nThis estimates how likely it is for groups of individuals to have similar\nphenotypes. To estimate this probability, we need three things:\n- a way to quantify phenotypic similarity of two individuals. We use the maximum\n information content of the most informative common ancestor for each pair of\n HPO terms from two probands.\n- a way to quantify similarity across more than two probands. We sum phenotypic\n similarity scores from all pairs of probands.\n- a null distribution of similarity scores for those probands, generated by\n randomly sampled groups of probands\n\nThe P value is calculated as the proportion of simulated scores greater than the\nobserved probands' score.\n\n##### Install\nInstall the package with:\n```sh\npip install hpo_similarity\n```\n\n##### Run\n```sh\nhpo_similarity --genes genes.json --phenotypes phenotypes.json\n```\nThe data directory on github includes example files, one with proband IDs\nper gene ([data/example_genes.json](data/example_genes.json)), and the other\nwith HPO terms per proband ([data/example_phenotypes.json](data/example_phenotypes.json)).\n\nAdditional options:\n- `--output PATH` to send output gene and P-values to a file.\n- `--ontology PATH` to use a HPO ontology file other than the default.\n- `--iterations INTEGER` to change the number of iterations (default=100000)\n\nYou can also explore the HPO graph using the hpo_similarity package within\npython, for example:\n```python\nfrom hpo_similarity import open_ontology\n\ngraph, alt_ids, obsolete_ids = open_ontology()\n\n# find all descendant terms\ngraph.get_descendants('HP:0001249')\n\n# get the text for the phenotypic abnormality\ngraph.nodes['HP:0001249']['name']\n```\n\n##### Acknowledgments\n This code incorporates the following code and datasets:\n - 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