rich_club: Rich club calculations

In brainGraph: Graph Theory Analysis of Brain MRI Data

Rich club calculations

Description

rich_club_coeff calculates the rich club of a graph, returning the rich-club coefficient, \phi, and the subgraph of rich club vertices.

rich_club_all is a wrapper for rich_club_coeff that calculates the rich-club coefficient for all degrees present in the graph. It returns a data.table with the coefficients and vertex and edge counts for each successive rich club.

rich_club_norm will (optionally) generate a number of random graphs, calculate their rich club coefficients (\phi), and return \phi_{norm} of the graph of interest, which is the observed rich-club coefficient divided by the mean across the random graphs.

rich_core finds the boundary of the rich core of a graph, based on the decreasing order of vertex degree. It also calculates the degree that corresponds to that rank, and the core size relative to the total number of vertices in the graph.

Usage

rich_club_coeff(g, k = 1, weighted = FALSE, A = NULL)

rich_club_all(g, weighted = FALSE, A = NULL)

rich_club_norm(g, N = 100, rand = NULL, ...)

rich_core(g, weighted = FALSE, A = NULL)

Arguments

g	An igraph graph object
k	Integer; the minimum degree for including a vertex. Default: 1
weighted	Logical indicating whether or not edge weights should be used. Default: FALSE
A	Numeric matrix; the adjacency matrix of the input graph. Default: NULL
N	Integer; the number of random graphs to generate. Default: 100
rand	A list of igraph graph objects, if random graphs have already been generated. Default: NULL
...	Other parameters (passed to sim.rand.graph.par)

Details

If random graphs have already been generated, you can supply a list as an argument.

For weighted graphs, the degree is substituted by a normalized weight:

ceiling(A / w_{min})

where w_{min} is the minimum weight (that is greater than 0), and ceiling() is the ceiling function that rounds up to the nearest integer.

Value

rich_club_coeff - a list with components:

phi	The rich club coefficient, \phi.
graph	A subgraph containing only the rich club vertices.
Nk, Ek	The number of vertices/edges in the rich club graph.

rich_club_all - a data.table with components:

k	A vector of all vertex degrees present in the original graph
phi	The rich-club coefficient
Nk, Ek	The number of vertices/edges in the rich club for each successive k

rich_club_norm - a data table with columns:

k	Sequence of degrees
rand	Rich-club coefficients for the random graphs
orig	Rich-club coefficients for the original graph.
norm	Normalized rich-club coefficients.
p	P-values based on the distribution of rand
p.fdr	The FDR-adjusted P-values
density	The observed graph's density
threshold, Group, name

rich_core - a data table with columns:

density	The density of the graph.
rank	The rank of the boundary for the rich core.
k.r	The degree/strength of the vertex at the boundary.
core.size	The size of the core relative to the graph size.
weighted	Whether or not weights were used

Author(s)

Christopher G. Watson, [e-mail]

References

Zhou, S. and Mondragon, R.J. (2004) The rich-club phenomenon in the internet topology. IEEE Comm Lett, 8, 180–182. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.4018/978-1-59140-993-9.ch066")}

Opsahl, T. and Colizza, V. and Panzarasa, P. and Ramasco, J.J. (2008) Prominence and control: the weighted rich-club effect. Physical Review Letters, 101.16, 168702. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1103/PhysRevLett.101.168702")}

Colizza, V. and Flammini, A. and Serrano, M.A. and Vespignani, A. (2006) Detecting rich-club ordering in complex networks. Nature Physics, 2, 110–115. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1038/nphys209")}

Ma, A and Mondragon, R.J. (2015) Rich-cores in networks. PLoS One, 10(3), e0119678. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1371/journal.pone.0119678")}

See Also

Other Rich-club functions: plot_rich_norm, rich_club_attrs

Other Random graph functions: Random Graphs

brainGraph documentation built on June 22, 2024, 7:36 p.m.