DOSE: Disease Ontology Semantic and Enrichment analysis

Disease Ontology (DO)(Schriml et al. 2011) aims to provide an open source ontology for the integration of biomedical data that is associated with human disease. We developed DOSE(Yu et al. 2015) package to promote the investigation of diseases. DOSE provides five methods including Resnik, Lin, Jiang, Rel and Wang for measuring semantic similarities among DO terms and gene products; Hypergeometric model and Gene Set Enrichment Analysis (GSEA) were also implemented for associating disease with gene list and extracting disease association insight from genome wide expression profiles.

The enrichment analyses support Disease Ontology (DO)(Schriml et al. 2011), Network of Cancer Gene (NCG)(A. et al. 2016) and DisGeNET(Janet et al. 2015). In addition, several visualization methods were provided by enrichplot to help interpreting semantic and enrichment results.

Citation

If you use DOSE in published research, please cite G. Yu (2015).

G Yu, LG Wang, GR Yan, QY He. DOSE: an R/Bioconductor package for Disease Ontology Semantic and Enrichment analysis. Bioinformatics 2015, 31(4):608-609. http://dx.doi.org/10.1093/bioinformatics/btu684.

Vignette

Please go to https://yulab-smu.github.io/clusterProfiler-book for the full vignette of enrichment analysis.

For semantic analysis, please go to https://bioconductor.org/packages/devel/bioc/vignettes/DOSE/inst/doc/semanticAnalysis.html.

Need helps?

If you have questions/issues, please visit DOSE homepage first. Your problems are mostly documented. If you think you found a bug, please follow the guide and provide a reproducible example to be posted on github issue tracker. For questions, please post to Bioconductor support site and tag your post with DOSE.

References

A., Omer, Giovanni M. D., Thanos P. M., and Francesca D. C. 2016. “NCG 5.0: Updates of a Manually Curated Repository of Cancer Genes and Associated Properties from Cancer Mutational Screenings.” Nucleic Acids Research 44 (D1): D992–D999. https://doi.org/10.1093/nar/gkv1123.

Janet, P., Núria Q. R., Àlex B., Jordi D. P., Anna B. M., Martin B., Ferran S., and Laura I. F. 2015. “DisGeNET: A Discovery Platform for the Dynamical Exploration of Human Diseases and Their Genes.” Database 2015 (March): bav028. https://doi.org/10.1093/database/bav028.

Schriml, L. M., C. Arze, S. Nadendla, Y.-W. W. Chang, M. Mazaitis, V. Felix, G. Feng, and W. A. Kibbe. 2011. “Disease Ontology: A Backbone for Disease Semantic Integration.” Nucleic Acids Research 40 (D1): D940–D946. https://doi.org/10.1093/nar/gkr972.

Yu, Guangchuang, Li-Gen Wang, Guang-Rong Yan, and Qing-Yu He. 2015. “DOSE: An R/Bioconductor Package for Disease Ontology Semantic and Enrichment Analysis.” Bioinformatics 31 (4): 608–9. https://doi.org/10.1093/bioinformatics/btu684.