GOSemSim: GO semantic similarity measurement

The semantic comparisons of Gene Ontology (GO) annotations provide quantitative ways to compute similarities between genes and gene groups, and have became important basis for many bioinformatics analysis approaches. GOSemSim is an R package for semantic similarity computation among GO terms, sets of GO terms, gene products and gene clusters. GOSemSim implemented five methods proposed by Resnik, Schlicker, Jiang, Lin and Wang respectively.

GOSemSim is released within the Bioconductor project and the source code is hosted on GitHub.

Author

Guangchuang Yu, School of Basic Medical Sciences, Southern Medical University.

Citation

Please cite the following article when using GOSemSim:

citation

Yu G†, Li F†, Qin Y, Bo X*, Wu Y and Wang S*. GOSemSim: an R package for measuring semantic similarity among GO terms and gene products. Bioinformatics. 2010, 26(7):976-978.

Installation

Install GOSemSim is easy, follow the guide in the Bioconductor page:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
## biocLite("BiocUpgrade") ## you may need this
biocLite("GOSemSim")

Overview

Methods

  • Information content based methods proposed by Resnik, Schlicker, Jiang and Lin
  • Graph structure based method proposed by Wang

Combine methods for aggregating multiple GO terms

  • max
  • avg
  • rcmax
  • BMA

Functions

  • goSim and mgoSim for measureing semantic similarity among GO terms
  • geneSim and mgeneSim for measureing semantic similarity among genes
  • clusterSim and mclusterSim for measureing semantic similarity among gene clusters

Supported organisms

  • 20 species that have OrgDb available in Bioconductor
  • Many other species with e GO annotation query online via AnnotationHub)

Find out details and examples on Documentation.

Projects that depend on GOSemSim

CRAN packages

  • BioMedR: Generating Various Molecular Representations for Chemicals, Proteins, DNAs, RNAs and Their Interactions
  • BiSEp: Toolkit to Identify Candidate Synthetic Lethality
  • LANDD: Liquid Association for Network Dynamics Detection

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