get_ligand_signaling_path_with_receptor: Get ligand-target signaling paths between ligand(s),...

In saeyslab/nichenetr: NicheNet: Modeling Intercellular Communication by Linking Ligands to Target Genes

Get ligand-target signaling paths between ligand(s), receptors, and target gene(s) of interest

Description

get_ligand_signaling_path_with_receptor Extract possible signaling paths between a ligand(s), receptor(s) and target gene(s) of interest. The most highly weighted path(s) will be extracted.

Usage

get_ligand_signaling_path_with_receptor(ligand_tf_matrix, ligands_all, receptors_all, targets_all, top_n_regulators = 3, weighted_networks, ligands_position = "cols")

Arguments

ligand_tf_matrix	A matrix of ligand-regulator probability scores
ligands_all	A character vector of one or more ligands of interest
receptors_all	A character vector of one or more receptors of interest
targets_all	A character vector of one or more target genes of interest
top_n_regulators	The number of top regulators that should be included in the ligand-target signaling network. Top regulators are regulators that score both high for being upstream of the target gene(s) and high for being downstream of the ligand. Default: 4.
weighted_networks	A list of two elements: lr_sig: a data frame/ tibble containg weighted ligand-receptor and signaling interactions (from, to, weight); and gr: a data frame/tibble containng weighted gene regulatory interactions (from, to, weight)
ligands_position	Indicate whether the ligands in the ligand-target matrix are in the rows ("rows") or columns ("cols"). Default: "cols".

Value

A list containing 2 elements (sig and gr): the integrated weighted ligand-signaling and gene regulatory networks data frame / tibble format with columns: from, to, weight

Examples

## Not run: 
weighted_networks = construct_weighted_networks(lr_network, sig_network, gr_network,source_weights_df)
ligands = list("TNF","BMP2",c("IL4","IL13"))
ligand_tf_matrix = construct_ligand_tf_matrix(weighted_networks, ligands, ltf_cutoff = 0.99, algorithm = "PPR", damping_factor = 0.5,ligands_as_cols = TRUE)
all_ligands = c("BMP2")
all_receptors = c("BMPR2")
all_targets = c("HEY1")
top_n_regulators = 2
ligand_target_signaling_list = get_ligand_signaling_path_with_receptor(ligand_tf_matrix,all_ligands,all_receptors, all_targets,top_n_regulators,weighted_networks)

## End(Not run)

saeyslab/nichenetr documentation built on April 27, 2024, 9:24 p.m.