Package: MODA 1.33.0

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_1.33.0.tar.gz
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MODA.pdf |MODA.html✨
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-1.33.0(bioc 3.21)MODA-1.32.0(bioc 3.20)

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 185 downloads 28 mentions 9 exports 107 dependencies

Last updated 23 days agofrom:1417781ef8. Checks:OK: 1 NOTE: 6. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Nov 18 2024
R-4.5-win	NOTE	Nov 18 2024
R-4.5-linux	NOTE	Nov 18 2024
R-4.4-win	NOTE	Nov 18 2024
R-4.4-mac	NOTE	Nov 18 2024
R-4.3-win	NOTE	Nov 18 2024
R-4.3-mac	NOTE	Nov 18 2024

Exports:CompareAllNets comparemodulestwonets ModuleFrequency PartitionDensity PartitionModularity WeightedModulePartitionAmoutain WeightedModulePartitionHierarchical WeightedModulePartitionLouvain WeightedModulePartitionSpectral

Dependencies:AMOUNTAIN AnnotationDbi askpass backports base64enc Biobase BiocGenerics Biostrings bit bit64 blob bslib cachem checkmate cli cluster codetools colorspace cpp11 crayon curl data.table DBI digest doParallel dynamicTreeCut evaluate fansi farver fastcluster fastmap fontawesome foreach foreign Formula fs generics GenomeInfoDb GenomeInfoDbData ggplot2 glue GO.db gridExtra gtable highr Hmisc htmlTable htmltools htmlwidgets httr igraph impute IRanges isoband iterators jquerylib jsonlite KEGGREST knitr labeling lattice lifecycle magrittr MASS Matrix matrixStats memoise mgcv mime munsell nlme nnet openssl pillar pkgconfig plogr png preprocessCore R6 rappdirs RColorBrewer Rcpp rlang rmarkdown rpart RSQLite rstudioapi S4Vectors sass scales stringi stringr survival sys tibble tinytex UCSC.utils utf8 vctrs viridis viridisLite WGCNA withr xfun XVector yaml zlibbioc

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