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dcanr

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

Differential co-expression/association network analysis


Bioconductor version: Development (3.19)

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 "4.4") 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")
1. Differential co-expression analysis HTML R Script
2. DC method evaluation HTML R Script
Reference Manual PDF
NEWS Text

Details

biocViews DifferentialExpression, GraphAndNetwork, Network, NetworkInference, Software
Version 1.19.0
In Bioconductor since BioC 3.9 (R-3.6) (5 years)
License GPL-3
Depends R (>= 3.6.0)
Imports igraph, foreach, plyr, stringr, reshape2, methods, Matrix, graphics, stats, RColorBrewer, circlize, doRNG
System Requirements
URL https://davislaboratory.github.io/dcanr/ https://github.com/DavisLaboratory/dcanr
Bug Reports https://github.com/DavisLaboratory/dcanr/issues
See More
Suggests EBcoexpress, testthat, EBarrays, GeneNet, mclust, minqa, SummarizedExperiment, Biobase, knitr, rmarkdown, BiocStyle, edgeR
Linking To
Enhances parallel, doSNOW, doParallel
Depends On Me
Imports Me multiWGCNA, SingscoreAMLMutations
Suggests Me
Links To Me
Build Report Build Report

Package Archives

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

Source Package dcanr_1.19.0.tar.gz
Windows Binary dcanr_1.19.0.zip
macOS Binary (x86_64) dcanr_1.19.0.tgz
macOS Binary (arm64) dcanr_1.19.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/dcanr
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/dcanr
Bioc Package Browser https://code.bioconductor.org/browse/dcanr/
Package Short Url https://bioconductor.org/packages/dcanr/
Package Downloads Report Download Stats