Package: GWENA 1.23.0

Gwenaëlle Lemoine

GWENA: Pipeline for augmented co-expression analysis

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.

Authors:Gwenaëlle Lemoine [aut, cre], Marie-Pier Scott-Boyer [ths], Arnaud Droit [fnd]

GWENA_1.23.0.tar.gz
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GWENA_1.23.0.tgz(r-4.6-any)GWENA_1.23.0.tgz(r-4.5-any)
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GWENA_1.23.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
GWENA/json (API)

# Install 'GWENA' in R:
install.packages('GWENA', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/kumquatum/gwena/issues

Datasets:
  • gtex_expr - Transcriptomic muscle data from GTEx consorsium RNA-seq data
  • gtex_traits - Traits data linked to samples in transcriptomic data from GTEx
  • kuehne_expr - Transcriptomic data from the Kuehne et al. publication
  • kuehne_traits - Traits data linked to samples in transcriptomic data from the Kuehne et al. publication

On BioConductor:GWENA-1.23.0(bioc 3.24)GWENA-1.22.0(bioc 3.23)

softwaregeneexpressionnetworkclusteringgraphandnetworkgenesetenrichmentpathwaysvisualizationrnaseqtranscriptomicsmrnamicroarraymicroarraynetworkenrichmentsequencinggoco-expressionenrichment-analysisgenenetwork-analysispipeline

5.88 score 25 stars 15 scripts 435 downloads 1 mentions 27 exports 113 dependencies

Last updated from:255a3b6c0f. Checks:8 WARNING, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksWARNING214
linux-devel-x86_64WARNING583
source / vignettesOK325
linux-release-x86_64WARNING635
macos-release-arm64WARNING362
macos-oldrel-arm64WARNING402
windows-develWARNING521
windows-releaseWARNING511
windows-oldrelWARNING496
wasm-releaseOK184

Exports:associate_phenotypebio_enrichbuild_graph_from_sq_matbuild_netcompare_conditionsdetect_modulesfilter_low_varfilter_RNA_seqget_fit.corget_fit.exprget_hub_degreeget_hub_genesget_hub_high_coget_hub_kleinbergget_sub_clustersis_data_expris_gostis_moduleis_networkjoin_gostplot_comparison_statsplot_enrichmentplot_expression_profilesplot_moduleplot_modules_mergeplot_modules_phenotypez_summary

Dependencies:abindaskpassbackportsbase64encBHBiobaseBiocGenericsbitopsbslibcachemcheckmatecliclustercodetoolscolorspacecpp11crosstalkcurldata.tableDelayedArraydigestdoParalleldplyrdynamicTreeCutevaluatefarverfastclusterfastmapfontawesomeforeachforeignFormulafsgenericsGenomicRangesggplot2gluegprofiler2gridExtragtablehighrHmischtmlTablehtmltoolshtmlwidgetshttrigraphimputeIRangesisobanditeratorsjquerylibjsonliteknitrlabelinglaterlatticelazyevallifecyclemagrittrMatrixMatrixGenericsmatrixStatsmemoisemimeNetRepnnetopensslotelpillarpkgconfigplotlypreprocessCorepromisespurrrR6rappdirsRColorBrewerRcppRcppArmadilloRCurlRhpcBLASctlrlangrlistrmarkdownrpartrstudioapiS4ArraysS4VectorsS7sassscalesSeqinfoSparseArraystatmodstringistringrSummarizedExperimentsurvivalsystibbletidyrtidyselecttinytexutf8vctrsviridisLiteWGCNAwithrxfunXMLXVectoryaml

GWENA - Tutorial

Gwenaëlle Lemoine

Rendered fromGWENA_guide.Rmdusingknitr::rmarkdownon May 23 2026.

Last update: 2021-06-24
Started: 2019-10-17

Readme and manuals

Help Manual

Help pageTopics
Run checks on an object to test if it's a data_expr.check_data_expr
Run checks on an object to test if it's a gost result.check_gost
Run checks on an object to test if it's a module or a list of modules.check_module
Run checks on an object to test if it's a network.check_network
Calculate a contigency table of module overlap between datasets.contingencyTable
Match a correlation function based on a name.cor_func_match
Modules phenotpic associationassociate_phenotype
Modules enrichmentbio_enrich
Return graph from squared matrix networkbuild_graph_from_sq_mat
Network building by co-expression score computationbuild_net
Compare modules topology between conditionscompare_conditions
Modules detection in a networkdetect_modules
Filtering genes with low variabilityfilter_low_var
Filtering of low countsfilter_RNA_seq
Calculating best fit of a power low on correlation matrix computed on expression dataget_fit.cor
Calculating best fit of a power low on expression dataget_fit.expr
Determine hub genes based on degreeget_hub_degree
Determine hub genes inside each moduleget_hub_genes
Determine hub genes based on connectivityget_hub_high_co
Determine hub genes based on Kleinberg's scoreget_hub_kleinberg
Detect sub clustersget_sub_clusters
Mimicking ggplot palette Source : https://stackoverflow.com/questions/8197559/emulate-ggplot2-default-color-palettegg_palette
Transcriptomic muscle data from GTEx consorsium RNA-seq datagtex_expr
Traits data linked to samples in transcriptomic data from GTExgtex_traits
Determine if an object is a data_expr in sens of GWENAis_data_expr
Determine if an object is a gost objectis_gost
Determine if an object is a module or a list of modulesis_module
Determine if an object is a networkis_network
Join gprofiler2::gost resultsjoin_gost
Transcriptomic data from the Kuehne et al. publicationkuehne_expr
Traits data linked to samples in transcriptomic data from the Kuehne et al. publicationkuehne_traits
Heatmap of comparison statisticsplot_comparison_stats
Plot module from bio_enrichplot_enrichment
Modules expression profilesplot_expression_profiles
Plot co-expression networkplot_module
Modules merge plotplot_modules_merge
Heatmap of modules phenotpic associationplot_modules_phenotype
Muting a functionquiet
Calculating Z summaryz_summary