rwr_SGprop: Single gene network based propagation based on random walk...

In LucaGiudice/Esearch3D: Leveraging gene expression and chromatin architecture to predict intergenic enhancers

Description

Performs the single gene propagation based on Random walk with restart. This operation is suggested to apply only after having performed the standard propagation based on all the genes with the two steps. First, overall propagation to diffuse expression of all genes included in a cell profile to genic fragments. Second, overall propagation to diffuse the propagated expression of all genes from genic fragments to intergenic.

Usage

rwr_SGprop(
  gf_net,
  ff_net,
  gene_in,
  input_m,
  frag_pattern = "frag",
  out_rda = "sg_prop.rda",
  degree = 4,
  r1 = 0.1,
  r2 = 0.8,
  no_cores = 2
)

Arguments

gf_net	Edge list of the chromatin interaction network such that first column are genes and second column are "FragX" fragments
ff_net	Edge list of the chromatin interaction network such that first and second column are "FragX" fragments
gene_in	Character vector of the genes of interest
input_m	numeric matrix of cell profile, one column of a cell, rows are genes or fragments, values are expression or IAS
frag_pattern	Character string to identify the fragments in the edge list (e.g. "FragX")
out_rda	Default: sg_prop.rda, Character string to define the output rda file which will contain all the results of the analysis and intermediate products
degree	Default 4, the degree of distance which is used to select the most important fragments connected to the genes of interest (e.g. degree 2 means G –> F1 –> F2)
r1	Default 0.1, A double value lower than 1 indicating the percentage of information that a gene keeps (0.1 is 10 percentage)
r2	Default 0.8, A double value lower than 1 indicating the percentage of information that a fragment keeps (0.8 is 80 percentage)
no_cores	Default 2, An integer value greater than 0 indicating the number of cores to use for parallel computing

Details

This function performs the propagation of individual genes of interest belonging to a cell's expression profile. It does not perform the standard propagation using all the genes of a cell profile. It then returns how much each gene of interest contributed to give information to the fragments. It then returns how much each fragment received information from the genes of interest. This function helps to understand the contribution of the individual genes in the two-step standard propagation.

Value

A list single_gene_prop composed of two sublists contr_lxDest: For each target node as element of the list, the vector of the seed nodes which gave information to it contr_lxOrig: For each seed node as element of the list, the vector of the targets nodes which receive information from it

LucaGiudice/Esearch3D documentation built on Dec. 17, 2021, 1:12 a.m.