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)MODA_1.39.0.zip(r-4.6)MODA_1.39.0.zip(r-4.5)
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✨
card.svg |card.png
MODA/json (API)
NEWS

# Install 'MODA' in R:

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

Datasets:

datExpr1 - DatExpr1
datExpr2 - DatExpr2

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.

geneexpression microarray differentialexpression network

3.30 score 9 scripts 371 downloads 28 mentions 9 exports 72 dependencies

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

Target	Result	Time
bioc-checks	ERROR	184
linux-devel-x86_64	NOTE	217
source / vignettes	OK	197
linux-release-x86_64	NOTE	211
macos-release-arm64	NOTE	157
macos-oldrel-arm64	NOTE	86
windows-devel	NOTE	483
windows-release	NOTE	111
windows-oldrel	NOTE	402
wasm-release	OK	145

Exports:CompareAllNets comparemodulestwonets ModuleFrequency PartitionDensity PartitionModularity WeightedModulePartitionAmoutain WeightedModulePartitionHierarchical WeightedModulePartitionLouvain WeightedModulePartitionSpectral

Dependencies:AMOUNTAIN backports base64enc bslib cachem checkmate cli cluster codetools colorspace cpp11 data.table digest doParallel dynamicTreeCut evaluate farver fastcluster fastmap fontawesome foreach foreign Formula fs ggplot2 glue gridExtra gtable highr Hmisc htmlTable htmltools htmlwidgets igraph impute isoband iterators jquerylib jsonlite knitr labeling lattice lifecycle magrittr Matrix matrixStats memoise mime nnet pkgconfig preprocessCore R6 rappdirs RColorBrewer Rcpp rlang rmarkdown rpart rstudioapi S7 sass scales stringi stringr survival tinytex vctrs viridisLite WGCNA withr xfun yaml

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Illustration of network comparison	CompareAllNets
Illustration of two networks comparison	comparemodulestwonets
datExpr1	datExpr1
datExpr2	datExpr2
Get numeric partition from folder	getPartition
Modules detection by each condition	MIcondition
Statistics of all conditions	ModuleFrequency
Modules rank from recursive communities detection	modulesRank
Illustration of network comparison by NMI	NMImatrix
Illustration of partition density	PartitionDensity
Illustration of modularity density	PartitionModularity
Modules identification by recursive community detection	recursiveigraph
Modules detection by AMOUNTAIN algorithm	WeightedModulePartitionAmoutain
Modules detection by hierarchical clustering	WeightedModulePartitionHierarchical
Modules detection by Louvain algorithm	WeightedModulePartitionLouvain
Modules detection by spectral clustering	WeightedModulePartitionSpectral