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.
Please cite the following article when using
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.
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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")
- 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
- 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
Projects that depend on GOSemSim
- clusterProfiler: statistical analysis and visualization of functional profiles for genes and gene clusters
- DOSE: Disease Ontology Semantic and Enrichment analysis
- meshes: MeSH Enrichment and Semantic analyses
- Rcpi: Molecular Informatics Toolkit for Compound-Protein Interaction in Drug Discovery
- tRanslatome: Comparison between multiple levels of gene expression