moduleIdentificationGPFixSS: Module Identification

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

Description

Algorithm for Module Identification on single network

Usage

moduleIdentificationGPFixSS(W, z, x0, a = 0.5, lambda = 1, maxiter = 1000)

Arguments

W	edge score matrix of the network, n x n matrix
z	node score vector of the network, n-length vector
x0	initial solution, n-length vector
a	parameter in elastic net the same as in EuclideanProjectionENNORM
lambda	parameter in objective, coefficient of node score part
maxiter	maximal interation of whole procedure

Value

a list containing function objective vector and the solution

Author(s)

Dong Li, [e-mail]

References

AMOUNTAIN

See Also

EuclideanProjectionENNORM

Examples

n = 100
k = 20
theta = 0.5
pp <- networkSimulation(n,k,theta)
moduleid <- pp[[3]]
## use default parameters here
x <- moduleIdentificationGPFixSS(pp[[1]],pp[[2]],rep(1/n,n))
predictedid<-which(x[[2]]!=0)
recall <- length(intersect(predictedid,moduleid))/length(moduleid)
precise <- length(intersect(predictedid,moduleid))/length(predictedid)
Fscore <- (2*precise*recall/(precise+recall))

fairmiracle/AMOUNTAIN documentation built on May 16, 2019, 9:59 a.m.