PyHPO documentationο
π Getting started:
π₯οΈ Examples:
PyHPOο
A Python library to work with, analyze, filter and inspect the Human Phenotype Ontology
Visit the PyHPO Documentation for a more detailed overview of all the functionality.
Main featuresο
π« Identify patient cohorts based on clinical features
π¨βπ§βπ¦ Cluster patients or other clinical information for GWAS
π©»β𧬠Phenotype to Genotype studies
ππ HPO similarity analysis
πΈοΈ Graph based analysis of phenotypes, genes and diseases
PyHPO allows working on individual terms HPOTerm, a set of terms HPOSet and the full Ontology.
The library is helpful for discovery of novel gene-disease associations and GWAS data analysis studies. At the same time, it can be used for oragnize clinical information of patients in research or diagnostic settings.
Internally the ontology is represented as a branched linked list, every term contains pointers to its parent and child terms. This allows fast tree traversal functionality.
It provides an interface to create Pandas Dataframe from its data, allowing integration in already existing data anlysis tools.
Hint
Check out hpo3 (Documentation) for an alternative implementation. hpo3 has the exact same functionality, but is much faster π and supports multithreading for even faster large data processing.