GOSemSim: GO semantic similarity measurement

Semantic similarity analysis of Gene Ontology (GO) annotations provides a quantitative framework for comparing GO terms, gene products, and gene clusters. GOSemSim implements widely used information content- and graph-based similarity measures, including the methods of Resnik, Schlicker, Jiang, Lin, Wang and TCSS. It also provides utilities for preparing annotation data and combining term-level similarities into gene- and cluster-level scores.

:writing_hand: Authors

Guangchuang YU https://yulab-smu.top

School of Basic Medical Sciences, Southern Medical University

Learn more at https://yulab-smu.top/contribution-knowledge-mining/.

If you use GOSemSim in published research, please cite:

• Yu G. Gene Ontology Semantic Similarity Analysis Using GOSemSim. In: Kidder B. (eds) Stem Cell Transcriptional Networks. Methods in Molecular Biology, 2020, 2117:207-215. Humana, New York, NY.
• 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.

:arrow_double_down: Installation

Get the released version from Bioconductor:

## try http:// if https:// URLs are not supported
if (!requireNamespace("BiocManager", quietly=TRUE))
    install.packages("BiocManager")
## BiocManager::install("BiocUpgrade") ## you may need this
BiocManager::install("GOSemSim")

Or the development version from github:

## install.packages("remotes")
remotes::install_github("YuLab-SMU/GOSemSim")

:sparkling_heart: Contributing

We welcome any contributions! By participating in this project you agree to abide by the terms outlined in the Contributor Code of Conduct.