| epc {centiserve} | R Documentation |
Find the edge percolated component (EPC) in a graph
Description
For a node v in G, EPC(v) is defined as:
EPC(v)=\frac{1}{\left|v\right|}\sum_{k=1}^{1000}\sum_{t\in e}\delta_{vt}^{k}
Given a threshold (0 \leq the threshold \leq 1), we create 1000 reduced network by asigning a random number between 0 and 1 to every edge and remove edges if their associated random numbers are less than the threshold.
Let the G_{k} be the reduced network generated at the k_{th} time reduced process. If nodes u and v are connected in G_{k}, set \delta_{vt}^{k} to 1; otherwise \delta_{vt}^{k}=0.
Usage
epc(graph, vids = V(graph), threshold = 0.5)
Arguments
graph |
The input graph as igraph object |
vids |
Vertex sequence, the vertices for which the centrality values are returned. Default is all vertices. |
threshold |
The threshold parameter, for filter graph and create reduced one, which must be between 0 and 1. The default is 0.5. |
Details
For an interaction network G, assign a removing probability p to every edge. Let G'be a realization of the random edge removing from G. If nodes v and w are connected in G', set d_{vw} be 1, otherwise set d_{vw} be 0. The percolated connectivity of v and w, c_{vw}, is defined to be the average of d_{vw} over realizations. The size of percolated component containing node v, s_{v}, is defined to be the sum of c_{vw} over nodes w. The score of node v, EPC(v), is defined to be s_{v}.
More detail at EPC-Edge Percolated Component
Value
A numeric vector contaning the centrality scores for the selected vertices.
Author(s)
Mahdi Jalili m_jalili@farabi.tums.ac.ir
References
Lin, Chung-Yen, et al. "Hubba: hub objects analyzer-a framework of interactome hubs identification for network biology." Nucleic acids research 36.suppl 2 (2008): W438-W443.
Chen, Shu-Hwa, et al. "cyto-Hubba: A Cytoscape plug-in for hub object analysis in network biology." 20th International Conference on Genome Informatics. 2009.
Examples
g <- graph(c(1,2,2,3,3,4,4,2))
epc(g)