ssMutPA (version 0.1.2)

MRWR: A global propagation algorithm, random walk with restart (RWR), to predict probable influence of nodes in the network by seed nodes.

Description

The function `MRWR` is used to predict probable influence of nodes in the network by seed nodes.

Usage

MRWR(
  net_AdjMatrNorm,
  Seeds,
  net_data,
  mut_gene,
  r = 0.7,
  BC_Num = length(V(net_data)$name),
  cut_point = 0
)

Value

An matrix of global weight, where the row names are genes in the network and the column names are samples.

Arguments

net_AdjMatrNorm

Row normalized network adjacency matrix.

Seeds

A vector containing the gene symbols of the seed nodes.

net_data

A list of the PPI network information,including nodes and edges .

mut_gene

A vector containing the gene symbols of the mutated genes in a sample.

r

A numeric value between 0 and 1. r is a certain probability of continuing the random walk or restarting from the restart set. Default to 0.7.

BC_Num

Number of background genes required to calculate seed node weight.

cut_point

The threshold of indicator function .

Examples

#load the data
net_path <- system.file("extdata","ppi_network.Rdata",package = "ssMutPA")
load(net_path)
net_AdjMatr<-as.matrix(igraph::get.adjacency(ppi_network))
net_AdjMatrNorm <- t(t(net_AdjMatr)/(Matrix::colSums(net_AdjMatr, na.rm = FALSE, dims = 1)))
data(mut_status)
mut_gene<-intersect(names(mut_status[,1])[which(mut_status[,1]!=0)],igraph::V(ppi_network)$name)
seed<-intersect(names(mut_status[,1])[which(mut_status[,1]!=0)],igraph::V(ppi_network)$name)
#perform the function `MRWR`.
RWR_res<-MRWR(net_AdjMatrNorm,Seeds=seed,net_data=ppi_network,mut_gene,BC_Num = 12436)