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


Bioconductor version: Development (3.19)

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.

Author: Dario Tommasini [aut, cre] , Brent Fogel [aut, ctb]

Maintainer: Dario Tommasini <dtommasini0 at>

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


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))

# The following initializes usage of Bioc devel


For older versions of R, please refer to the appropriate Bioconductor release.


Reference Manual PDF


biocViews Clustering, DifferentialExpression, GeneExpression, RNASeq, Regression, Sequencing, Software
Version 1.1.3
In Bioconductor since BioC 3.18 (R-4.3) (< 6 months)
License GPL-3
Depends R (>= 4.3.0), ggalluvial
Imports stringr, readr, WGCNA, dplyr, reshape2, data.table, patchwork, scales, igraph, flashClust, ggplot2, dcanr, cowplot, ggrepel, methods, SummarizedExperiment
System Requirements
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Suggests BiocStyle, doParallel, ExperimentHub, knitr, markdown, rmarkdown, testthat (>= 3.0.0), vegan
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Follow Installation instructions to use this package in your R session.

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