title: HPOSim: an R package for phenotypic similarity measure and enrichment analysis based on the human phenotype ontology.
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/).
authors: School of Computer Science and Technology, Xidian University, Xi'an, People's Republic of China; Institute of Software Engineering, Xidian University, Xi'an, People's Republic of China.
authors: Yue
authors: Y
authors: Deng
authors: School of Computer Science and Technology, Xidian University, Xi'an, People's Republic of China.
authors: Lin
authors: L
authors: Gao
authors: School of Computer Science and Technology, Xidian University, Xi'an, People's Republic of China.
authors: Bingbo
authors: B
authors: Wang
authors: School of Computer Science and Technology, Xidian University, Xi'an, People's Republic of China.
authors: Xingli
authors: X
authors: Guo
mesh_terms: D019295:Computational Biology; D030541:Databases, Genetic; D004194:Disease / Q000235:genetics*; D063990:Gene Ontology; D005796:Genes; D020022:Genetic Predisposition to Disease; D006801:Humans; D010641:Phenotype; D012984:Software