moduleIdentificationGPFixSSTwolayer {AMOUNTAIN} | R Documentation

## Module Identification for two-layer network

### Description

Algorithm for Module Identification on two-layer network

### Usage

    moduleIdentificationGPFixSSTwolayer(W1, z1, x0, W2, z2, y0, A, lambda1 = 1,
      lambda2 = 1, lambda3 = 1, maxiter = 1000, a1 = 0.5, a2 = 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
`a1` | parameter in elastic net the same as in `EuclideanProjectionENNORM`
`a2` | parameter in elastic net the same as in `EuclideanProjectionENNORM`

### Value

a list containing solution for network 1 and network 2 and objective

### Author(s)

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

### References

AMOUNTAIN

### See Also

`EuclideanProjectionENNORM`

### Examples

    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)

[Package AMOUNTAIN version 1.6.0 Index]