dcanr

DOI: 10.18129/B9.bioc.dcanr    

This is the development version of dcanr; for the stable release version, see dcanr.

Differential co-expression/association network analysis

Bioconductor version: Development (3.17)

This package implements methods and an evaluation framework to infer differential co-expression/association networks. Various methods are implemented and can be evaluated using simulated datasets. Inference of differential co-expression networks can allow identification of networks that are altered between two conditions (e.g., health and disease).

Author: Dharmesh D. Bhuva [aut, cre]

Maintainer: Dharmesh D. Bhuva <bhuva.d at wehi.edu.au>

Citation (from within R, enter citation("dcanr")):

Installation

To install this package, start R (version "4.3") and enter:

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

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("dcanr")

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("dcanr")

 

HTML R Script 1. Differential co-expression analysis
HTML R Script 2. DC method evaluation
PDF   Reference Manual
Text   NEWS

Details

biocViews DifferentialExpression, GraphAndNetwork, Network, NetworkInference, Software
Version 1.15.0
In Bioconductor since BioC 3.9 (R-3.6) (3.5 years)
License GPL-3
Depends R (>= 3.6.0)
Imports igraph, foreach, plyr, stringr, reshape2, methods, Matrix, graphics, stats, RColorBrewer, circlize, doRNG
LinkingTo
Suggests EBcoexpress, testthat, EBarrays, GeneNet, mclust, minqa, SummarizedExperiment, Biobase, knitr, rmarkdown, BiocStyle, edgeR
SystemRequirements
Enhances parallel, doSNOW, doParallel
URL https://davislaboratory.github.io/dcanr/ https://github.com/DavisLaboratory/dcanr
BugReports https://github.com/DavisLaboratory/dcanr/issues
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report  

Package Archives

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

Source Package dcanr_1.15.0.tar.gz
Windows Binary dcanr_1.15.0.zip
macOS Binary (x86_64) dcanr_1.15.0.tgz
macOS Binary (arm64)
Source Repository git clone https://git.bioconductor.org/packages/dcanr
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/dcanr
Package Short Url https://bioconductor.org/packages/dcanr/
Package Downloads Report Download Stats

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