DOSE

DOI: 10.18129/B9.bioc.DOSE    

Disease Ontology Semantic and Enrichment analysis

Bioconductor version: Release (3.13)

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.

Author: Guangchuang Yu [aut, cre], Li-Gen Wang [ctb], Vladislav Petyuk [ctb], Giovanni Dall'Olio [ctb], Erqiang Hu [ctb]

Maintainer: Guangchuang Yu <guangchuangyu at gmail.com>

Installation

To install this package, start R (version "4.1") and enter:

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

BiocManager::install("DOSE")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("DOSE")

 

HTML	R Script	DOSE
PDF		Reference Manual
Text		NEWS

Details

biocViews	Annotation, GeneSetEnrichment, MultipleComparison, Pathways, Software, Visualization
Version	3.18.3
In Bioconductor since	BioC 2.9 (R-2.14) (10 years)
License	Artistic-2.0
Depends	R (>= 3.5.0)
Imports	AnnotationDbi, BiocParallel, DO.db, fgsea, ggplot2, GOSemSim(>= 2.0.0), methods, qvalue, reshape2, stats, utils
LinkingTo
Suggests	prettydoc, clusterProfiler, knitr, rmarkdown, org.Hs.eg.db, testthat
SystemRequirements
Enhances
URL	https://yulab-smu.top/biomedical-knowledge-mining-book/
BugReports	https://github.com/GuangchuangYu/DOSE/issues
Depends On Me
Imports Me	bioCancer, clusterProfiler, debrowser, eegc, enrichplot, GDCRNATools, meshes, miRspongeR, MoonlightR, ReactomePA, RegEnrich, RNASeqR, scTensor, signatureSearch
Suggests Me	cola, GOSemSim, MAGeCKFlute, rrvgo, scGPS, simplifyEnrichment
Links To Me
Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package	DOSE_3.18.3.tar.gz
Windows Binary	DOSE_3.18.3.zip
macOS 10.13 (High Sierra)	DOSE_3.18.3.tgz
Source Repository	git clone https://git.bioconductor.org/packages/DOSE
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/DOSE
Package Short Url	https://bioconductor.org/packages/DOSE/
Package Downloads Report	Download Stats
Old Source Packages for BioC 3.13	Source Archive