DOSE: Disease Ontology Semantic and Enrichment analysis

Provides ontology-aware methods for disease and phenotype knowledge mining. DOSE supports semantic similarity analysis of disease and phenotype ontology terms, genes, and gene clusters using methods including Resnik, Schlicker, Jiang, Lin, and Wang. It also provides over-representation analysis and gene set enrichment analysis for interpreting gene vectors and ranked gene lists in disease, phenotype, and cancer contexts.

✍️ 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/.

⏬ Installation

Get the released version from Bioconductor:

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("DOSE")

Or install the development version from GitHub:

if (!requireNamespace("remotes", quietly = TRUE))
    install.packages("remotes")
remotes::install_github("YuLab-SMU/DOSE")

Please cite the following article when using DOSE:

Guangchuang Yu, Li-Gen Wang, Guang-Rong Yan, Qing-Yu He. DOSE: an R/Bioconductor package for Disease Ontology Semantic and Enrichment analysis. Bioinformatics. 2015, 31(4):608-609.

💖 Contributing

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