HPOSim: an R package for phenotypic similarity measure and enrichment analysis based on the human phenotype ontology

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) provide...

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Bibliographic Details
Published in:PloS one 2015-02, Vol.10 (2), p.e0115692-e0115692
Main Authors: Deng, Yue, Gao, Lin, Wang, Bingbo, Guo, Xingli
Format: Article
Language:English
Subjects:
Abnormalities
Aging
Annotations
Apoptosis
Bioinformatics
Computational Biology
Computer applications
Computer programs
Computer science
Consortia
Databases, Genetic
Disease
Disease - genetics
Diseases
Enrichment
Gene Ontology
Genes
Genetic Predisposition to Disease
Genotype & phenotype
Heredity
Humans
International conferences
Online databases
Ontology
Phenotype
Phenotypes
Semantics
Similarity
Similarity measures
Skin cancer
Software
Software development tools
Taxonomy
Vocabularies & taxonomies
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Summary: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. 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). 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/).
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0115692