nichenet_ligand_activities: Calls the NicheNet ligand activity analysis

In saezlab/OmnipathR: OmniPath web service client and more

Calls the NicheNet ligand activity analysis

Description

Calls the NicheNet ligand activity analysis

Usage

nichenet_ligand_activities(
  ligand_target_matrix,
  lr_network,
  expressed_genes_transmitter,
  expressed_genes_receiver,
  genes_of_interest,
  background_genes = NULL,
  n_top_ligands = 42,
  n_top_targets = 250
)

Arguments

ligand_target_matrix	A matrix with rows and columns corresponding to ligands and targets, respectively. Produced by nichenet_ligand_target_matrix or nichenetr::construct_ligand_target_matrix.
lr_network	A data frame with ligand-receptor interactions, as produced by nichenet_lr_network.
expressed_genes_transmitter	Character vector with the gene symbols of the genes expressed in the cells transmitting the signal.
expressed_genes_receiver	Character vector with the gene symbols of the genes expressed in the cells receiving the signal.
genes_of_interest	Character vector with the gene symbols of the genes of interest. These are the genes in the receiver cell population that are potentially affected by ligands expressed by interacting cells (e.g. genes differentially expressed upon cell-cell interaction).
background_genes	Character vector with the gene symbols of the genes to be used as background.
n_top_ligands	How many of the top ligands to include in the ligand-target table.
n_top_targets	For each ligand, how many of the top targets to include in the ligand-target table.

Value

A named list with 'ligand_activities' (a tibble giving several ligand activity scores; following columns in the tibble: $test_ligand, $auroc, $aupr and $pearson) and 'ligand_target_links' (a tibble with columns ligand, target and weight (i.e. regulatory potential score)).

Examples

## Not run: 
networks <- nichenet_networks()
expression <- nichenet_expression_data()
optimization_results <- nichenet_optimization(networks, expression)
nichenet_model <- nichenet_build_model(optimization_results, networks)
lt_matrix <- nichenet_ligand_target_matrix(
    nichenet_model$weighted_networks,
    networks$lr_network,
    nichenet_model$optimized_parameters
)
ligand_activities <- nichenet_ligand_activities(
    ligand_target_matrix = lt_matrix,
    lr_network = networks$lr_network,
    # the rest of the parameters should come
    # from your transcriptomics data:
    expressed_genes_transmitter = expressed_genes_transmitter,
    expressed_genes_receiver = expressed_genes_receiver,
    genes_of_interest = genes_of_interest
)

## End(Not run)

saezlab/OmnipathR documentation built on Nov. 10, 2024, 11:02 p.m.