dcanr
This is the released version of dcanr; for the devel version, see dcanr.
Differential co-expression/association network analysis
Bioconductor version: Release (3.20)
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("dcanr")
):
Installation
To install this package, start R (version "4.4") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
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 | ||
NEWS | Text |
Details
biocViews | DifferentialExpression, GraphAndNetwork, Network, NetworkInference, Software |
Version | 1.22.0 |
In Bioconductor since | BioC 3.9 (R-3.6) (5.5 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_1.22.0.tar.gz |
Windows Binary (x86_64) | dcanr_1.22.0.zip |
macOS Binary (x86_64) | dcanr_1.22.0.tgz |
macOS Binary (arm64) | dcanr_1.22.0.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 |