grn_infer: Infer gene regulatory network with one of three algorithms

In almeidasilvaf/BioNERO: Biological Network Reconstruction Omnibus

Infer gene regulatory network with one of three algorithms

Description

The available algorithms are Context Likelihood of Relatedness (CLR), ARACNE, or GENIE3.

Usage

grn_infer(
  exp,
  regulators = NULL,
  method = c("clr", "aracne", "genie3"),
  estimator_clr = "pearson",
  estimator_aracne = "spearman",
  eps = 0.1,
  remove_zero = TRUE,
  ...
)

Arguments

exp	A gene expression data frame with genes in row names and samples in column names or a 'SummarizedExperiment' object.
regulators	A character vector of regulators (e.g., transcription factors or miRNAs). All regulators must be included in 'exp'.
method	GRN inference algorithm to be used. One of "clr", "aracne", or "genie3".
estimator_clr	Entropy estimator to be used. One of "mi.empirical", "mi.mm", "mi.shrink", "mi.sg", "pearson", "spearman", or "kendall". Default: "pearson".
estimator_aracne	Entropy estimator to be used. One of "mi.empirical", "mi.mm", "mi.shrink", "mi.sg", "pearson", "spearman", or "kendall". Default: "spearman".
eps	Numeric value indicating the threshold used when removing an edge: for each triplet of nodes (i,j,k), the weakest edge, say (ij), is removed if its weight is below min(ik),(jk) - eps. Default: 0.1.
remove_zero	Logical indicating whether to remove edges whose weight is exactly zero. Default: TRUE
...	Additional arguments passed to 'GENIE3::GENIE3()'.

Value

A gene regulatory network represented as an edge list.

Examples

data(filt.se)
tfs <- sample(rownames(filt.se), size=20, replace=FALSE)
clr <- grn_infer(filt.se, method = "clr", regulators=tfs)
aracne <- grn_infer(filt.se, method = "aracne", regulators=tfs)
# only 2 trees for demonstration purposes
genie3 <- grn_infer(filt.se, method = "genie3", regulators=tfs, nTrees=2)

almeidasilvaf/BioNERO documentation built on March 25, 2024, 9:14 p.m.