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GWENA

Pipeline for augmented co-expression analysis

Bioconductor version: 3.24 · Package version: 1.23.0

The development of high-throughput sequencing led to increased use of co-expression analysis to go beyong single feature (i.e. gene) focus. We propose GWENA (Gene Whole co-Expression Network Analysis) , a tool designed to perform gene co-expression network analysis and explore the results in a single pipeline. It includes functional enrichment of modules of co-expressed genes, phenotypcal association, topological analysis and comparison of networks configuration between conditions.

Installation

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("GWENA")

Details

MaintainerGwenaƫlle Lemoine <lemoine.gwenaelle@gmail.com>
AuthorGwenaƫlle Lemoine [aut, cre] (ORCID: <https://orcid.org/0000-0003-4747-1937>), Marie-Pier Scott-Boyer [ths], Arnaud Droit [fnd]
LicenseGPL-3
Bug Reportshttps://github.com/Kumquatum/GWENA/issues
Downloads rank471
Source branchdevel
biocViewsClustering, GO, GeneExpression, GeneSetEnrichment, GraphAndNetwork, Microarray, Network, NetworkEnrichment, Pathways, RNASeq, Sequencing, Software, Transcriptomics, Visualization, mRNAMicroarray

Documentation

Download

Follow the installation instructions to use this package in your R session.

Source packageGWENA_1.23.0.tar.gz
Windows binary (x86_64)GWENA_1.23.0.zip
macOS binary (arm64)GWENA_1.23.0.tgz
macOS binary (x86_64)GWENA_1.23.0.tgz
Dependencies

Depends: R (>= 4.1)

Imports: WGCNA (>= 1.67), dplyr (>= 0.8.3), dynamicTreeCut (>= 1.63-1), ggplot2 (>= 3.1.1), gprofiler2 (>= 0.1.6), magrittr (>= 1.5), tibble (>= 2.1.1), tidyr (>= 1.0.0), NetRep (>= 1.2.1), igraph (>= 1.2.4.1), RColorBrewer (>= 1.1-2), purrr (>= 0.3.3), rlist (>= 0.4.6.1), matrixStats (>= 0.55.0), SummarizedExperiment (>= 1.14.1), stringr (>= 1.4.0), cluster (>= 2.1.0), grDevices (>= 4.0.4), methods, graphics, stats, utils

Suggests: testthat (>= 2.1.0), knitr (>= 1.25), rmarkdown (>= 1.16), prettydoc (>= 0.3.0), httr (>= 1.4.1), S4Vectors (>= 0.22.1), BiocStyle (>= 2.15.8)