Package: multiWGCNA 1.5.0
Dario Tommasini
multiWGCNA: multiWGCNA
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.
Authors:
multiWGCNA_1.5.0.tar.gz
multiWGCNA_1.5.0.zip(r-4.5)multiWGCNA_1.5.0.zip(r-4.4)multiWGCNA_1.5.0.zip(r-4.3)
multiWGCNA_1.5.0.tgz(r-4.4-any)multiWGCNA_1.5.0.tgz(r-4.3-any)
multiWGCNA_1.5.0.tar.gz(r-4.5-noble)multiWGCNA_1.5.0.tar.gz(r-4.4-noble)
multiWGCNA_1.5.0.tgz(r-4.4-emscripten)multiWGCNA_1.5.0.tgz(r-4.3-emscripten)
multiWGCNA.pdf |multiWGCNA.html✨
multiWGCNA/json (API)
NEWS
| # Install 'multiWGCNA' in R: |
| install.packages('multiWGCNA', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
- permutationTestResults - Permutation test results
On BioConductor:multiWGCNA-1.5.0(bioc 3.21)multiWGCNA-1.4.0(bioc 3.20)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
sequencingrnaseqgeneexpressiondifferentialexpressionregressionclustering
Last updated 4 months agofrom:b2881a45d6. Checks:1 OK, 6 NOTE. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Feb 03 2025 |
| R-4.5-win | NOTE | Feb 03 2025 |
| R-4.5-linux | NOTE | Feb 03 2025 |
| R-4.4-win | NOTE | Feb 03 2025 |
| R-4.4-mac | NOTE | Feb 03 2025 |
| R-4.3-win | NOTE | Feb 03 2025 |
| R-4.3-mac | NOTE | Feb 03 2025 |
Exports:bidirectionalBestMatchescleanDatExprcoexpressionLineGraphcomputeOverlapsFromWGCNAconstructNetworksdiffCoexpressiondiffModuleExpressiondrawMultiWGCNAnetworkGetDatExprgetPreservationiteratemakeTraitTablemoduleComparisonPlotmoduleExpressionPlotmoduleToModuleHeatmapnameoverlapComparisonsperformANOVApreservationComparisonPlotpreservationComparisonsPreservationPermutationTestPreservationScoreDistributionrunDMEsummarizeResultsTOMFlowPlottopNGenes
Dependencies:abindAnnotationDbiaskpassbackportsbase64encBiobaseBiocGenericsBiostringsbitbit64blobbslibcachemcheckmatecirclizeclicliprclustercodetoolscolorspacecowplotcpp11crayoncurldata.tableDBIdcanrDelayedArraydigestdoParalleldoRNGdplyrdynamicTreeCutevaluatefansifarverfastclusterfastmapflashClustfontawesomeforeachforeignFormulafsgenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggalluvialggplot2ggrepelGlobalOptionsglueGO.dbgridExtragtablehighrHmischmshtmlTablehtmltoolshtmlwidgetshttrigraphimputeIRangesisobanditeratorsjquerylibjsonliteKEGGRESTknitrlabelinglatticelazyevallifecyclemagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemgcvmimemunsellnlmennetopensslpatchworkpillarpkgconfigplogrplyrpngpreprocessCoreprettyunitsprogresspurrrR6rappdirsRColorBrewerRcppreadrreshape2rlangrmarkdownrngtoolsrpartRSQLiterstudioapiS4ArraysS4VectorssassscalesshapeSparseArraystringistringrSummarizedExperimentsurvivalsystibbletidyrtidyselecttinytextzdbUCSC.utilsutf8vctrsviridisviridisLitevroomWGCNAwithrxfunXVectoryaml
multiWGCNA: visualizing condition-specific networks
Rendered fromastrocyte_map_v2.Rmdusingknitr::rmarkdownon Feb 03 2025.Last update: 2024-02-20
Started: 2023-06-06
multiWGCNA: the full workflow
Rendered fromautism_full_workflow.Rmdusingknitr::rmarkdownon Feb 03 2025.Last update: 2024-05-05
Started: 2023-06-30
