Get a set of predicted target genes of a ligand of interest

get_target_genes_ligand_oi Get a set of predicted target genes of a ligand of interest.

Usage

get_target_genes_ligand_oi(ligand_oi, ligand_target_matrix, error_rate = 0.1, cutoff_method = "distribution", fdr_method = "global", output = "logical",ligands_position = "cols")

Arguments

ligand_oi

The ligand of interest of which top target genes should be returned

ligand_target_matrix

A matrix of ligand-target probabilty scores.

error_rate

FDR for cutoff_method "fdrtool" and "distribution"; number between 0 and 1 indicating which top fraction of target genes should be returned for cutoff_method "quantile". Default: 0.1

cutoff_method

Method to determine which genes can be considered as a target of a ligand and which genes not, based on the ligand-target probability scores. Possible options: "distribution", "fdrtool" and "quantile". Default: "distribution".

fdr_method

Only relevant when cutoff_method is "fdrtool". Possible options: "global" and "local". Default: "global".

output

Determines whether a vector with target gene names should be returned ("gene_symbols") or a logical vector indicating for every target gene whether or not it is a target ("logical").

ligands_position

Indicate whether the ligands in the ligand-target matrix are in the rows ("rows") or columns ("cols"). Default: "cols"

Value

A vector with target gene names should be returned ("gene_symbols") or a logical vector indicating for every target gene whether or not it is a target ("logical").

Examples

if (FALSE) { # \dontrun{
## Generate the ligand-target matrix from loaded weighted_networks
weighted_networks <- construct_weighted_networks(lr_network, sig_network, gr_network, source_weights_df)
ligands <- list("TNF", "BMP2", c("IL4", "IL13"))
ligand_target_matrix <- construct_ligand_target_matrix(weighted_networks, lr_network, ligands)
targets <- get_target_genes_ligand_oi("BMP2", ligand_target_matrix, error_rate = 0.1, cutoff_method = "distribution", fdr_method = "global", output = "logical", ligands_position = "cols")
} # }