rwrProp: Network based propagation based on Random walk with restart

In LucaGiudice/Simpati: Pathway-based classifier exploits patient similarity network paradigm

Description

This function performs propagation of the patient's profiles passed as columns of a matrix

Usage

rwrProp(
  net,
  geno,
  norm = "row",
  n_cores = 2,
  r = 0.8,
  stop_step = 200,
  stop_delta = 1e-06,
  keep_zero_profiles = FALSE,
  keep_no_nodes = FALSE
)

Arguments

net	Gene interaction network as adjacency matrix
geno	Numeric matrix of genetic profiles
norm	Default row, options: row or column or laplacian, it indicates the graph normalization performed on the network
n_cores	Default 2, An integer value greater than 0 indicating the number of cores to use for parallel computing
r	Default 0.8, A double value lower than 1 indicating the percentage of information that a gene keeps (0.8 is 80 percentage)
stop_step	Default 200, An integer value greater than 0 indicating the number of iterations of the propagation
stop_delta	Default 1e-06, A double value lower than 0 indicating the threshold under which all imputed propagation values are set 0
keep_zero_profiles	Default FALSE, Boolean: TRUE if to keep profiles without information
keep_no_nodes	Default FALSE, Boolean: TRUE if to keep profile's rows without node in the network

Value

A list with elements describing the input data which are by the method

LucaGiudice/Simpati documentation built on Jan. 27, 2022, 11:42 p.m.