Phenotypic clustering is a computational approach for grouping diseases based on shared phenotypic characteristics, offering insights into disease relationships, similarities, and underlying biological mechanisms. This repository hosts a Python script designed to perform phenotypic clustering by identifying common phenotypes among different diseases using Human Phenotype Ontology Annotation (HPOA) data. The script parses HPOA files, groups diseases by database ID, and compares their associated phenotypes to determine similarities, utilizing multiprocessing techniques for efficient computation.
Phenotypic clustering has diverse applications in biomedical research and clinical practice, aiding in disease classification, gene prioritization, comorbidity identification, and drug repurposing. Users can employ the script to analyze their own disease datasets, facilitating the discovery of disease clusters and informing research and clinical decision-making.