DRW: Directed Random Walk

Description Usage Arguments Details Value Author(s) References Examples

View source: R/DRW.R

Description

The directed random walk algorithm proposed by Liu et al(2013).

Usage

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DRW(igraphM, p0, EdgeWeight = FALSE, gamma = 0.3)

Arguments

igraphM

An igraph object containing the directed global pathway graph.

p0

A unit vector containing the initial weights of genes in the global pathway graph.

EdgeWeight

Logical. Should igraphM be converted to a weighted matrix or an un-weighted matrix (the default)?

gamma

A numeric value. The restart probability in directed random walk.

Details

This function implements the directed random walk algorithm proposed by Liu et al (2013). It evaluates the topological weight of each gene according to its topological importance in the global pathway graph. The genes that close to many other genes that have large initial weights will receive larger weights. The final weights reflect the topological importances of genes in the global pathway graph.

Value

A numerical vector containing the topological weights of nodes in igraphM.

Author(s)

Wei Liu <[email protected]>

References

Liu, W., et al., Topologically inferring risk-active pathways toward precise cancer classification by directed random walk. Bioinformatics, 2013. 29(17): p. 2169-77.

Examples

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  data(dGMGraph)
  vertexs <- V(dGMGraph)
  p0 <- runif(length(vertexs), min = 0, max = 1)
  names(p0) <- vertexs$name
  p0 <- p0/sum(p0)
  vertexWeight <- DRW(igraphM = dGMGraph, p0=p0, EdgeWeight=FALSE, gamma = 0.3)
  names(vertexWeight) <- names(p0)

cuihaibo1/drwPSurv_1.0.tar documentation built on May 12, 2017, 2:21 p.m.