network_thresholding: Thresholds a non sparse adjascency matrix to return the...

In OceaneCsn/DIANE: DIANE

Thresholds a non sparse adjascency matrix to return the strongest weights only

Description

Without thresholding, we would obtain a fully connected weighted graph from GENIE3, with far too many links to be interpretable. In order build a meaningful network, this weighted adjacency matrix between regulators and targets has to be sparsified, and we have to determine the regulatory weights that we consider significant.

This method is a nice exploratory way to threshold complete networks, but to get more robust and significant results, consider using the DIANE::test_edges() function.

Usage

network_thresholding(mat, n_edges)

Arguments

mat	matrix containing the importance values for each target and regulator, as returned by DIANE::network_inference()
n_edges	number of edges top edges to keep in the final network.

Value

igraph object representing the Gene Regulatory Network

Examples

## Not run: 
data("abiotic_stresses")
data("regulators_per_organism")
genes <- get_locus(abiotic_stresses$heat_DEGs)
# mat was inferred using the function network_inference
mat <- abiotic_stresses$heat_DEGs_regulatory_links
network <- DIANE::network_thresholding(mat, n_edges = length(genes))

## End(Not run)

OceaneCsn/DIANE documentation built on Jan. 10, 2024, 6:43 p.m.