multiWGCNA
multiWGCNA
Bioconductor version: 3.24 · Package version: 1.11.0
An R package for deeping mining gene co-expression networks in multi-trait expression data. Provides functions for analyzing, comparing, and visualizing WGCNA networks across conditions. multiWGCNA was designed to handle the common case where there are multiple biologically meaningful sample traits, such as disease vs wildtype across development or anatomical region.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("multiWGCNA")Details
| Maintainer | Dario Tommasini <dtommasini0@gmail.com> |
| Author | Dario Tommasini [aut, cre] (ORCID: <https://orcid.org/0000-0002-1214-6547>), Brent Fogel [aut, ctb] |
| License | GPL-3 |
| Downloads rank | 361 |
| Source branch | devel |
| biocViews | Clustering, DifferentialExpression, GeneExpression, RNASeq, Regression, Sequencing, Software |
Documentation
Download
Follow the installation instructions to use this package in your R session.
| Source package | multiWGCNA_1.11.0.tar.gz |
| Windows binary (x86_64) | multiWGCNA_1.11.0.zip |
| macOS binary (arm64) | multiWGCNA_1.11.0.tgz |
| macOS binary (x86_64) | multiWGCNA_1.11.0.tgz |
Dependencies
Depends: R (>= 4.3.0), ggalluvial
Imports: stringr, readr, WGCNA, magrittr, dplyr, reshape2, data.table, patchwork, scales, igraph, flashClust, ggplot2, dcanr, cowplot, ggrepel, methods, SummarizedExperiment, ggraph, tidyr
Suggests: BiocStyle, doParallel, ExperimentHub, knitr, markdown, rmarkdown, testthat (>= 3.0.0), vegan
Reverse dependencies
Suggests Me (1): multiWGCNAdata