In aiminy/ModifiedDOSE: Disease Ontology Semantic and Enrichment analysis

BiocStyle::markdown()
knitr::opts_chunk$set(tidy = FALSE,
                      warning = FALSE,
                      message = FALSE)

library(DOSE)

Disease Ontology (DO)[@schriml_disease_2011] aims to provide an open source ontology for the integration of biomedical data that is associated with human disease. We developed r Biocpkg("DOSE")[@yu_dose_2015] package to promote the investigation of diseases. r Biocpkg("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 extracting disease association insight from genome wide expression profiles.

Citation

If you use r Biocpkg("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.

Overview

r Biocpkg("DOSE") provides five methods for measureing semantic similarity among DO terms and genes. It implemented over-representation analysis to associate disease with gene list (e.g. differential expressed genes) and gene set enrichment analysis to associate disease with genome wide expression profiles. The enrichment analyses support Disease Ontology (DO)[@schriml_disease_2011], Network of Cancer Gene (NCG)[@omer_ncg] and DisGeNET[@janet_disgenet]. In addition, several visualization methods were developed to help interpreting semantic and enrichment results.