dcanr
Differential co-expression/association network analysis
Bioconductor version: 3.23 · Package version: 1.28.0
Other Bioconductor versions
devel is the development version; release is the current stable one.
3.24 (devel), 3.23 (release)
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).
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("dcanr")Details
| Maintainer | Dharmesh D. Bhuva <bhuva.d@wehi.edu.au> |
| Author | Dharmesh D. Bhuva [aut, cre] (ORCID: <https://orcid.org/0000-0002-6398-9157>) |
| License | GPL-3 |
| URL | https://davislaboratory.github.io/dcanr/, https://github.com/DavisLaboratory/dcanr |
| Bug Reports | https://github.com/DavisLaboratory/dcanr/issues |
| Source branch | RELEASE_3_23 |
| Build report | Bioconductor build system, r-universe |
| biocViews | DifferentialExpression, GraphAndNetwork, Network, NetworkInference, Software |
| Package Short Url | https://bioconductor.org/packages/dcanr/ |
Citation
From within R, enter citation("dcanr"):
Dharmesh D. Bhuva. dcanr: Differential co-expression/association network analysis. doi:10.18129/B9.bioc.dcanr, R package version 1.28.0, https://bioconductor.org/packages/dcanr.
Generated from the package metadata; it may differ from the package's own citation.
Documentation
- Performing differential co-expression analysis using dcanr
- Evaluating differential co-expression methods using dcanr
Download
Follow the installation instructions to use this package in your R session.
| Source package | dcanr_1.28.0.tar.gz |
| Windows binary (x86_64) | dcanr_1.28.0.zip |
| macOS binary (arm64) | dcanr_1.28.0.tgz |
| macOS binary (x86_64) | dcanr_1.28.0.tgz |
Dependencies
Depends: R (>= 3.6.0)
Imports: igraph, foreach, plyr, stringr, reshape2, methods, Matrix, graphics, stats, RColorBrewer, circlize, doRNG
Suggests: EBcoexpress, testthat, EBarrays, GeneNet, mclust, minqa, SummarizedExperiment, Biobase, knitr, rmarkdown, BiocStyle, edgeR
Enhances: parallel, doSNOW, doParallel
Reverse dependencies
Imports Me (2): ClassifyR, multiWGCNA