MODA: MODA: MOdule Differential Analysis for weighted gene co-expression network
Version 1.2.0

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.

AuthorDong Li, James B. Brown, Luisa Orsini, Zhisong Pan, Guyu Hu and Shan He
Bioconductor views DifferentialExpression GeneExpression Microarray Network
Date of publicationNone
MaintainerDong Li <dxl466@cs.bham.ac.uk>
LicenseGPL (>= 2)
Version1.2.0
Package repositoryView on Bioconductor
InstallationInstall the latest version of this package by entering the following in R:
source("https://bioconductor.org/biocLite.R")
biocLite("MODA")

Getting started

Usage of MODA"

Popular man pages

CompareAllNets: Illustration of network comparison
comparemodulestwonets: Illustration of two networks comparison
datExpr1: datExpr1
NMImatrix: Illustration of network comparison by NMI
PartitionDensity: Illustration of partition density
PartitionModularity: Illustration of modularity density
WeightedModulePartitionAmoutain: Modules detection by AMOUNTAIN algorithm
See all...

All man pages Function index File listing

Man pages

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

Functions

Files

DESCRIPTION
NAMESPACE
R
R/MODA.R
R/util.R
data
data/synthetic.RData
inst
inst/NEWS
inst/doc
inst/doc/Bibliography.bib
inst/doc/MODA.Rmd
inst/doc/MODA.html
man
man/CompareAllNets.Rd
man/MIcondition.Rd
man/ModuleFrequency.Rd
man/NMImatrix.Rd
man/PartitionDensity.Rd
man/PartitionModularity.Rd
man/WeightedModulePartitionAmoutain.Rd
man/WeightedModulePartitionHierarchical.Rd
man/WeightedModulePartitionLouvain.Rd
man/WeightedModulePartitionSpectral.Rd
man/comparemodulestwonets.Rd
man/datExpr1.Rd
man/datExpr2.Rd
man/getPartition.Rd
man/modulesRank.Rd
man/recursiveigraph.Rd
vignettes
vignettes/Bibliography.bib
vignettes/MODA.Rmd
MODA documentation built on May 20, 2017, 10:04 p.m.

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