assess_rf_class_probabilities: Assess probability that a target gene belongs to the geneset...

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

Assess probability that a target gene belongs to the geneset based on a multi-ligand random forest model

Description

assess_rf_class_probabilities Assess probability that a target gene belongs to the geneset based on a multi-ligand random forest model (with cross-validation). Target genes and background genes will be split in different groups in a stratified way.

Usage

assess_rf_class_probabilities(round,folds,geneset,background_expressed_genes,ligands_oi,ligand_target_matrix)

Arguments

round	Integer describing which fold of the cross-validation scheme it is.
folds	Integer describing how many folds should be used.
geneset	Character vector of the gene symbols of genes of which the expression is potentially affected by ligands from the interacting cell.
background_expressed_genes	Character vector of gene symbols of the background, non-affected, genes (can contain the symbols of the affected genes as well).
ligands_oi	Character vector giving the gene symbols of the ligands you want to build the multi-ligand with.
ligand_target_matrix	The NicheNet ligand-target matrix denoting regulatory potential scores between ligands and targets (ligands in columns).

Value

A tibble with columns: $gene, $response, $prediction. Response indicates whether the gene belongs to the geneset of interest, prediction gives the probability this gene belongs to the geneset according to the random forest model.

Examples

## Not run: 
weighted_networks = construct_weighted_networks(lr_network, sig_network, gr_network,source_weights_df)
ligands = list("TNF","BMP2","IL4")
ligand_target_matrix = construct_ligand_target_matrix(weighted_networks, ligands, ltf_cutoff = 0, algorithm = "PPR", damping_factor = 0.5, secondary_targets = FALSE)
potential_ligands = c("TNF","BMP2","IL4")
geneset = c("SOCS2","SOCS3", "IRF1")
background_expressed_genes = c("SOCS2","SOCS3","IRF1","ICAM1","ID1","ID2","ID3")
fold1_rf_prob = assess_rf_class_probabilities(round = 1,folds = 2,geneset = geneset,background_expressed_genes = background_expressed_genes ,ligands_oi = potential_ligands,ligand_target_matrix = ligand_target_matrix)

## End(Not run)

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