| markovcent {centiserve} | R Documentation |
Find the markov centrality score
Description
The Markov centrality score uses the concept of a random walk through the graph to calculate the centrality of each vertex.
Usage
markovcent(graph, vids = V(graph))
Arguments
graph |
The input graph as igraph object |
vids |
Vertex sequence, the vertices for which the markov centrality values are returned. |
Details
The method uses the mean first-passage time from every vertex to every other vertex to produce a score for each vertex.
More detail at Markov Centrality
Value
A numeric vector contaning the centrality scores for the selected vertices.
Author(s)
Mahdi Jalili m_jalili@farabi.tums.ac.ir
Original code from Bioconductor SANTA package (Cornish AJ, 2014)
References
White, S. & Smyth, P. Algorithms for estimating relative importance in networks. Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining, 2003. ACM, 266-275.
Cornish AJ and Markowetz F (2014). "SANTA: Quantifying the Functional Content of Molecular Networks." PLOS Computational Biology, 10(9), pp. e1003808. http://dx.doi.org/10.1371/journal.pcbi.1003808.
Examples
g <- graph(c(1,2,2,3,3,4,4,2))
markovcent(g)