Package: GmicR 1.27.0
GmicR: Combines WGCNA and xCell readouts with bayesian network learrning to generate a Gene-Module Immune-Cell network (GMIC)
This package uses bayesian network learning to detect relationships between Gene Modules detected by WGCNA and immune cell signatures defined by xCell. It is a hypothesis generating tool.
Authors:
GmicR_1.27.0.tar.gz
GmicR_1.27.0.zip(r-4.7)GmicR_1.27.0.zip(r-4.6)GmicR_1.27.0.zip(r-4.5)
GmicR_1.27.0.tgz(r-4.6-any)GmicR_1.27.0.tgz(r-4.5-any)
GmicR_1.27.0.tar.gz(r-4.7-any)GmicR_1.27.0.tar.gz(r-4.6-any)
GmicR_1.27.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
GmicR/json (API)
| # Install 'GmicR' in R: |
| install.packages('GmicR', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
On BioConductor:GmicR-1.27.0(bioc 3.24)GmicR-1.26.0(bioc 3.23)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
softwaresystemsbiologygraphandnetworknetworknetworkinferenceguiimmunooncologygeneexpressionqualitycontrolbayesianclustering
Last updated from:50be1b0ae8. Checks:1 ERROR, 7 WARNING, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| bioc-checks | ERROR | 247 | ||
| linux-devel-x86_64 | WARNING | 771 | ||
| source / vignettes | OK | 690 | ||
| linux-release-x86_64 | WARNING | 816 | ||
| macos-release-arm64 | WARNING | 454 | ||
| macos-oldrel-arm64 | WARNING | 431 | ||
| windows-devel | WARNING | 627 | ||
| windows-release | WARNING | 735 | ||
| windows-oldrel | WARNING | 701 | ||
| wasm-release | OK | 245 |
Exports:Auto_WGCNABatch_Netbn_tabu_genData_PrepGmic_vizGO_Module_NameRGSEAGO_BuilderInverseARCsQuery_PrepxCell_loader
Dependencies:annotateAnnotationDbiAnnotationForgeapeaskpassbackportsbase64encBHBiobaseBiocGenericsBiostringsbitbit64bitopsblobbnlearnbroombslibcachemCategorycheckmatecliclustercodetoolscolorspacecommonmarkcpp11crayoncrosstalkcurldata.tableDBIdigestdoParalleldplyrDTdynamicTreeCutevaluatefarverfastclusterfastmapfontawesomeforeachforeignFormulafsgenefiltergenericsggplot2glueGO.dbGOstatsgRaingraphgRbasegridExtraGSEABasegtablehighrHmischtmlTablehtmltoolshtmlwidgetshttpuvhttrigraphimputeIRangesisobanditeratorsjquerylibjsonliteKEGGRESTknitrlabelinglaterlatticelazyevallifecyclemagrittrMatrixMatrixGenericsmatrixStatsmemoisemimenlmennetopensslorg.Hs.eg.dborg.Mm.eg.dbotelpillarpkgconfigplyrpngpreprocessCorepromisespurrrR6rappdirsRBGLRColorBrewerRcppRcppArmadilloRcppEigenRCurlreshape2RgraphvizrlangrmarkdownrpartRSQLiterstudioapiS4VectorsS7sassscalesSeqinfoshinysourcetoolsstringistringrsurvivalsystibbletidyrtidyselecttinytexutf8vctrsviridisLiteWGCNAwithrxfunXMLxtableXVectoryaml
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Carries out WGCNA with default settings or custom settings | Auto_WGCNA |
| Generates a subgraph from query nodes | Batch_Net |
| Uses tabu search algorithm to learn the structure of discretized data. | bn_tabu_gen |
| Discretizes biological assay data in preparation for bayensian network learning | Data_Prep |
| Visualized network | Gmic_viz |
| GO enrichment for module names | GO_Module_NameR |
| GO enrichment for module names | GSEAGO_Builder |
| Identifies arcs between nodes with inverse relationships | InverseARCs |
| Query Prep | Query_Prep |
| Scales and centers data by sample/row in preparation for discretization | xCell_loader |
