NetPreProc (version 1.2)

Chua.norm-methods: Chua normalization

Description

Normalization of graphs according to Chua et al., 2007. The normalized weigths between nodes are computed by taking into account their neighborhoods. This normalization is meaningful in particular with interaction data. More precisely, the normalized weigth \(W_{ij}\) between nodes \(i\) and \(j\) is computed by taking into account their neighborhods \(N_i\) and \(N_j\) :

$$W_{ij} = \frac{2|N_i \cap N_j|}{|N_i \setminus N_j| + 2|N_i \cap N_j| + 1}\times \frac{2|N_i \cap N_j|}{|N_j \setminus N_i| + 2|N_i \cap N_j| + 1}$$ where \(N_k\) is the set of the neighbors of gene \(k\) (\(k\) is included).

Usage

Chua.norm(W)

Value

The normalized adjacency matrix of the network

Arguments

W

an object representing the graph to be normalized

Methods

signature(W = "graph")

an object of the virtual class graph (hence including objects of class graphAM and graphNEL from the package graph)

signature(W = "matrix")

a matrix representing the adjacency matrix of the graph

References

Chua, H., Sung, W., & Wong, L. An efficient strategy for extensive integration of diverse biological data for protein function prediction. Bioinformatics, 23 , 3364--3373, 2007.

Examples

library(bionetdata);
data(Yeast.Biogrid.data);
W <- Chua.norm(Yeast.Biogrid.data);