Chua.norm-methods {NetPreProc} | R Documentation |
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
andgraphNEL
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);