localClusteringCoefficient: Calculate the local clustering coefficient
In PCIT: Partial Correlation Coefficient with Information Theory

Description Usage Arguments Value Author(s) References See Also Examples

Calculate the local clustering coefficient for each node in an adjacency matrix. The clustering coefficient is defined as the proportion of existing connections from the total possible (Watts and Strogatz, 1998).

1	localClusteringCoefficient(adj)

adj

- An adjacency matrix. Calculating the clustering coefficient only makes sense if some connections are zero i.e. no connection.

A vector of local clustering coefficients for each node/gene of the adjacency matrix.

Nathan S. Watson-Haigh

D.J. Watts and S.H. Strogatz. (1998) Collective dynamics of 'small-world' networks. Nature. 393(6684). 440-442.

clusteringCoefficient

	data(PCIT)
	m <- m[1:200,1:200]        # just use a small subset of the data
	result <- pcit(m)
	m[idx(result)] <- 0
	
	localClusteringCoefficient(m)