network_filter_edges: Matrix filter edges

In drostlab/edgynode: Comparison of Gene Regulatory Networks

Matrix filter edges

Description

This function takes a weighted adjacency matrix filters out the unsignificant edges

Usage

network_filter_edges(
  adj_mat,
  threshold = NULL,
  print_message = TRUE,
  p_value = 0.1
)

Arguments

adj_mat	adjacency matrix to be converted.
threshold	if not specified, the function will filter based on the disparity measure (Neal, Z.P. (2022). backbone: An R package to extract network backbones) (recommended). If you want to specify threshold, we recommended to use network_rescale before using this function. Re-scaling will transform all values into a range [0,100]. The threshold can either be a numeric balue in the interval [0,100] or a character string specifying the following methods for automatically determining the threshold based on the input data:
print_message	a logical value indicating whether or not a threshold message shall be printed.
p_value	a value between setting the treshold for hypothesis testing for the backbone filtering.

Author(s)

Nikola Kalábová, Sergio Vasquez and Hajk-Georg Drost

Examples

 # path to PPCOR output file
ppcor_output <- system.file('beeline_examples/PPCOR/outFile.txt', package = 'edgynode')
 # import PPCOR specific output
ppcor_parsed <- ppcor(ppcor_output)
 # rescale the matrix
ppcor_rescaled <- network_rescale(ppcor_parsed)
 # make the binary matrix
ppcor_binary <- network_make_binary(ppcor_rescaled)
 # to see the differences you may use:
 plot_network_dendrogram(ppcor_rescaled)
 plot_network_dendrogram(ppcor_binary)

drostlab/edgynode documentation built on March 29, 2024, 10:36 a.m.