clustcoef_signed_mult: Calculate signed clustering coeffecient for a list of graphs.

In abnormally-distributed/rsfcNet: Analyze resting state functional connectivity networks

Description

Calculate the signed clustering coeffecient (local transitivity) for a list of graphs using either the Zhang & Horvath method or the Constantini & Perugini method.

Usage

clustcoef_signed_mult(graphs, method = "Constantini")

Arguments

graphs	A list of igraph objects or matrices.
method	Either "Constantini" (the default) or "Zhang"

Details

Calculate the signed clustering coeffecient (local transitivity) for a single graph using either the Zhang & Horvath (2005) method or the Constantini & Perugini (2014) method. The local transitivity (or clustering coeffecient) of a node is the fraction of edges a node forms with its neighbors out of the the number of edges it would take to make complete triangles. This code was adapted from the code in the qgraph package with modifications to make the output as in the matlab script clustering_coef_w_sign in the Brain Connectivity Toolbox. The Onella method is excluded due to similarities with the Barrat (available as the local_clustcoef function in this package) and Zhang methods.

Value

A matrix of clustering scores for each node and each subject

Author(s)

Brandon Vaughan

References

Brain Connectivity Toolbox

Costantini, G., & Perugini, M. (2014). Generalization of Clustering Coefficients to Signed Correlation Networks. PLoS ONE, 9(2), e88669. http://doi.org/10.1371/journal.pone.0088669

Zhang, B., & Horvath, S. (2005). A general framework for weighted gene co-expression network analysis. Statistical Applications in Genetics and Molecular Biology, 4(1).

See Also

local_trans transitivity clustcoef_signed

Examples

**##Not run**
clustcoef_signed_mult(graphs)
## End(**Not run**)

abnormally-distributed/rsfcNet documentation built on March 8, 2020, 5:32 p.m.