Chua.norm-methods: Chua normalization

In NetPreProc: Network Pre-Processing and Normalization

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)

Arguments

W	an object representing the graph to be normalized

Value

The normalized adjacency matrix of the network

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);

NetPreProc documentation built on Sept. 19, 2022, 5:06 p.m.