ModifiedDOSE: Disease Ontology Semantic and Enrichment analysis

This package implements five methods proposed by Resnik, Schlicker, Jiang, Lin and Wang respectively for measuring semantic similarities among DO terms and gene products. Enrichment analyses including hypergeometric model and gene set enrichment analysis are also implemented for discovering disease associations of high-throughput biological data.

DOSE is released within the Bioconductor project and the source code is hosted in GitHub.

Guangchuang Yu, School of Public Health, The University of Hong Kong.

Please cite the following article when using DOSE:

Yu G, Wang L, Yan G and He QY*. DOSE: an R/Bioconductor package for Disease Ontology Semantic and Enrichment analysis. Bioinformatics, 2015, 31(4):608-609.

Find out more on Featured Articles.

Install DOSE 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("DOSE")

Semantic similarity measurement

DO term semantic similarity
Gene semantic similarity

Enrichment Analysis

DO (Disease Ontology)
NCG (Network of Cancer Genes)
DisGeNet (gene-disease and SNP-disease associations)

Visualization

barplot
cnetplot
dotplot
enrichMap
gseaplot
simplot
upsetplot

Find out details and examples on Documentation.

clusterProfiler for Ontologies/pathways enrichment analyses
GOSemSim for GO semantic similarity measurement
meshes for MeSH Enrichment and Semantic analysis
ReactomePA for Reactome pathway analysis

Find out more on projects.

Please make sure you follow the guide before posting any issue/question
For bugs or feature requests, please post to github issue
For user questions, please post to Bioconductor support site and Biostars. We are following every post tagged with DOSE
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