twolayernetworkSimulation: Illustration of two-layer weighted network simulation

In AMOUNTAIN: Active modules for multilayer weighted gene co-expression networks: a continuous optimization approach

Description

Simulate a two-layer weighted network

Usage

twolayernetworkSimulation(n1, k1, theta1, n2, k2, theta2)

Arguments

n1	number of nodes in the network1
k1	number of nodes in the module1, n1 < k1
theta1	module1 node score follow the uniform distribution in range [theta1,1]
n2	number of nodes in the network2
k2	number of nodes in the module2, n2 < k2
theta2	module2 node score follow the uniform distribution in range [theta2,1]

Value

a list containing network1, network2 and a inter-layer links matrix

Author(s)

Dong Li, [e-mail]

See Also

networkSimulation

Examples

n1=100
k1=20
theta1 = 0.5
n2=80
k2=10
theta2 = 0.5
ppresult <- twolayernetworkSimulation(n1,k1,theta1,n2,k2,theta2)
A <- ppresult[[3]]
pp <- ppresult[[1]]
moduleid <- pp[[3]]
netid <- 1:n1
restp<- netid[-moduleid]
pp2 <- ppresult[[2]]
moduleid2 <- pp2[[3]]
netid2 <- 1:n2
restp2<- netid2[-moduleid2]
## labelling the groups
groupdesign=list(moduleid,restp,(moduleid2+n1),(restp2+n1))
names(groupdesign)=c('module1','background1','module2','background2')
twolayernet<-matrix(0,nrow=(n1+n2),ncol=(n1+n2))
twolayernet[1:n1,1:n1]<-pp[[1]]
twolayernet[(n1+1):(n1+n2),(n1+1):(n1+n2)]<-pp2[[1]]
twolayernet[1:n1,(n1+1):(n1+n2)] = A
twolayernet[(n1+1):(n1+n2),1:n1] = t(A)
## Not run: library(qgraph)
g<-qgraph(twolayernet,groups=groupdesign,legend=TRUE)
## End(Not run)

AMOUNTAIN documentation built on Nov. 8, 2020, 5:28 p.m.