moduleIdentificationGPFixSSMultilayer: Module Identification for multi-layer network

Description Usage Arguments Value Author(s) References See Also Examples

View source: R/AMOUNTAIN.R

Description

Algorithm for Module Identification on multi-layer network sharing the same set of genes

Usage

1
2
moduleIdentificationGPFixSSMultilayer(W, listz, x0, a = 0.5, lambda = 1,
  maxiter = 1000)

Arguments

W

edge score matrix of the network, n x n matrix

listz

a list of node score vectors, each layer has a 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 of other layers

maxiter

maximal interation of whole procedure

Value

a list containing objective values and solution

Author(s)

Dong Li, dxl466@cs.bham.ac.uk

References

AMOUNTAIN

See Also

moduleIdentificationGPFixSSMultilayer

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
n = 100
k = 20
L = 5
theta = 0.5
cpl <- multilayernetworkSimulation(n,k,theta,L)
listz <- list()
for (i in 1:L){
listz[[i]] <- cpl[[i+2]]
}
moduleid <- cpl[[2]]
## use default parameters here
x <- moduleIdentificationGPFixSSMultilayer(cpl[[1]],listz,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))

AMOUNTAIN documentation built on May 31, 2017, 2:46 p.m.