Description Usage Arguments Value Author(s) References See Also Examples
Algorithm for Module Identification on two-layer network
1 2 | moduleIdentificationGPFixSSTwolayer(W1, z1, x0, W2, z2, y0, A, lambda1 = 1,
lambda2 = 1, lambda3 = 1, maxiter = 1000, a1 = 0.5, a2 = 0.5)
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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 |
a1 |
parameter in elastic net the same as in |
a2 |
parameter in elastic net the same as in |
a list containing solution for network 1 and network 2 and objective
Dong Li, dxl466@cs.bham.ac.uk
AMOUNTAIN
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)
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