Package: MODA 1.39.0

Dong Li

MODA: MODA: MOdule Differential Analysis for weighted gene co-expression network

MODA can be used to estimate and construct condition-specific gene co-expression networks, and identify differentially expressed subnetworks as conserved or condition specific modules which are potentially associated with relevant biological processes.

Authors:Dong Li, James B. Brown, Luisa Orsini, Zhisong Pan, Guyu Hu and Shan He

MODA_1.39.0.tar.gz
MODA_1.39.0.zip(r-4.7-any)MODA_1.39.0.zip(r-4.6-any)MODA_1.39.0.zip(r-4.5-any)
MODA_1.39.0.tgz(r-4.6-any)MODA_1.39.0.tgz(r-4.5-any)
MODA_1.39.0.tar.gz(r-4.7-any)MODA_1.39.0.tar.gz(r-4.6-any)
MODA_1.39.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
MODA/json (API)

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

On BioConductor:MODA-1.39.0(bioc 3.24)MODA-1.38.0(bioc 3.23)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

geneexpressionmicroarraydifferentialexpressionnetwork

3.30 score 7 scripts 400 downloads 28 mentions 9 exports 72 dependencies

Last updated from:063275205f. Checks:1 ERROR, 7 NOTE, 2 OK. Indexed: yes.

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macos-releaseNOTE120
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windows-develNOTE105
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wasm-releaseOK122

Exports:CompareAllNetscomparemodulestwonetsModuleFrequencyPartitionDensityPartitionModularityWeightedModulePartitionAmoutainWeightedModulePartitionHierarchicalWeightedModulePartitionLouvainWeightedModulePartitionSpectral

Dependencies:AMOUNTAINbackportsbase64encbslibcachemcheckmatecliclustercodetoolscolorspacecpp11data.tabledigestdoParalleldynamicTreeCutevaluatefarverfastclusterfastmapfontawesomeforeachforeignFormulafsggplot2gluegridExtragtablehighrHmischtmlTablehtmltoolshtmlwidgetsigraphimputeisobanditeratorsjquerylibjsonliteknitrlabelinglatticelifecyclemagrittrMatrixmatrixStatsmemoisemimennetpkgconfigpreprocessCoreR6rappdirsRColorBrewerRcpprlangrmarkdownrpartrstudioapiS7sassscalesstringistringrsurvivaltinytexvctrsviridisLiteWGCNAwithrxfunyaml