Module Identification for two-layer network

Description

Algorithm for Module Identification on two-layer network

Usage

1
2
moduleIdentificationGPFixSSTwolayer(W1, z1, x0, W2, z2, y0, A, lambda1 = 1,
  lambda2 = 1, lambda3 = 1, maxiter = 1000, a = 0.5)

Arguments

W1

edge score matrix of the network 1, n_1 x n_1 matrix

z1

node score vector of the network 1, n_1-length vector

x0

initial solution of network 1, n_1-length vector

W2

edge score matrix of the network 2, n_2 x n_2 matrix

z2

node score vector of the network 2, n_2-length vector

y0

initial solution of network 2, n_2-length vector

A

inter-layer links weight, n_1 x n_2 matrix

lambda1

parameter in objective, coefficient of node score of network 1

lambda2

parameter in objective, coefficient of node score of network 2

lambda3

parameter in objective, coefficient of inter-layer links part

maxiter

maximal interation of whole procedure

a

parameter in elastic net the same as in EuclideanProjectionENNORM

Value

a list containing solution for network 1 and network 2

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
12
13
14
15
16
17
18
19
20
21
22
23
24
25
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]]
## use default parameters here
modres=moduleIdentificationGPFixSSTwolayer(pp[[1]],pp[[2]],rep(1/n1,n1),
pp2[[1]],pp2[[2]],rep(1/n2,n2),A)
predictedid<-which(modres[[1]]!=0)
recall = length(intersect(predictedid,moduleid))/length(moduleid)
precise = length(intersect(predictedid,moduleid))/length(predictedid)
F1 = 2*precise*recall/(precise+recall)
predictedid2<-which(modres[[2]]!=0)
recall2 = length(intersect(predictedid2,moduleid2))/length(moduleid2)
precise2 = length(intersect(predictedid2,moduleid2))/length(predictedid2)
F2 = 2*precise2*recall2/(precise2+recall2)