netCombo: NetCombo

In abhik1368/netpredictor: Algorithms to search for missing link in a graph.

Description

Peforms computation three different algorithms like random walk, network based inference and heterogenous based inference and finally computes the sum of the predicted score and generates the final matrix.

Usage

netCombo(g1, s1, s2, nbi.alpha = 0.4, nbi.lamda = 0.5, norm = "laplace",
  restart = 0.8, par = TRUE)

Arguments

g1	igraph object
s1	Accepts a matrix object of similarity scores for targets.
s2	Accepts a matrix object similarity scores for compounds.
nbi.alpha	alpha value for network based inference.
nbi.lamda	lamda value for network based inference.
norm	normalization of matrices options are "laplace" or "none".
restart	restart parameter for RWR
par	parallel execution for RWR.

Details

NetCombo

Value

Matrix object with sum score values.

Examples

data(Enzyme)
A = enzyme_ADJ
S1 = as.matrix(enzyme_Gsim)
S2 = as.matrix(enzyme_Csim)
g1 = graph.incidence(A)
P <- netCombo(g1,s1=S1,s2=S2,nbi.alpha=0.5,nbi.lamda=0.5,par=TRUE)
## With a different restart
P <- netCombo(g1,s1=S1,s2=S2,nbi.alpha=0.5,nbi.lamda=0.5,restart=0.7,par=TRUE)

abhik1368/netpredictor documentation built on May 10, 2019, 4:09 a.m.