Module Identification

Share:

Description

Algorithm for Module Identification on single network

Usage

1
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, dxl466@cs.bham.ac.uk

References

MOUNTAIN

See Also

EuclideanProjectionENNORM

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
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))