HPOSim: an R Package for Phenotypic Similarity Measure and Enrichment Analysis Based on the Human Phenotype Ontology

Overview

Journal PLoS One

Specialties General Medicine
Science

Date 2015 Feb 10

PMID 25664462

Citations 32

Authors

Yue Deng

Lin Gao

Bingbo Wang

Xingli Guo

Affiliations

Soon will be listed here.

Abstract

Background: Phenotypic features associated with genes and diseases play an important role in disease-related studies and most of the available methods focus solely on the Online Mendelian Inheritance in Man (OMIM) database without considering the controlled vocabulary. The Human Phenotype Ontology (HPO) provides a standardized and controlled vocabulary covering phenotypic abnormalities in human diseases, and becomes a comprehensive resource for computational analysis of human disease phenotypes. Most of the existing HPO-based software tools cannot be used offline and provide only few similarity measures. Therefore, there is a critical need for developing a comprehensive and offline software for phenotypic features similarity based on HPO.

Results: HPOSim is an R package for analyzing phenotypic similarity for genes and diseases based on HPO data. Seven commonly used semantic similarity measures are implemented in HPOSim. Enrichment analysis of gene sets and disease sets are also implemented, including hypergeometric enrichment analysis and network ontology analysis (NOA).

Conclusions: HPOSim can be used to predict disease genes and explore disease-related function of gene modules. HPOSim is open source and freely available at SourceForge (https://sourceforge.net/p/hposim/).

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