Run NicheNet analysis

Usage

RunNichenetr(
  object,
  group.by,
  receiver,
  sender = "all",
  condition.by = NULL,
  condition_oi = NULL,
  condition_reference = NULL,
  receiver_affected = NULL,
  receiver_reference = NULL,
  mode = c("aggregate", "aggregate_cluster_de", "custom"),
  assay = NULL,
  expression_pct = 0.1,
  geneset = NULL,
  background_expressed_genes = NULL,
  top_n_ligands = 30,
  top_n_targets = 200,
  species = c("Homo_sapiens", "Mus_musculus"),
  lr_network = NULL,
  ligand_target_matrix = NULL,
  weighted_networks = NULL,
  cutoff_visualization = 0.33,
  lfc_cutoff = 0.25,
  use_sender_agnostic_background = TRUE,
  backend = c("cpp", "r"),
  verbose = TRUE,
  srt = NULL,
  merged_table_file = NULL
)

Arguments

object: A Seurat object.
group.by: Metadata column defining cell types.
receiver: Receiver cell type(s).
sender: Sender cell type(s). Use "all" to use all non-receiver cell types.
condition.by: Metadata column defining conditions.
condition_oi: Condition of interest.
condition_reference: Reference condition.
receiver_affected: Affected receiver cell type(s) for mode = "aggregate_cluster_de". Defaults to receiver when NULL.
receiver_reference: Reference receiver cell type(s) for mode = "aggregate_cluster_de". Defaults to receiver when NULL.
mode: NicheNet wrapper mode. Supported values are "aggregate", "aggregate_cluster_de", and "custom".
assay: Assay to use.
expression_pct: Minimum fraction of cells expressing a gene.
geneset: Optional target gene set for mode = "custom".
background_expressed_genes: Optional background genes for mode = "custom".
top_n_ligands: Number of top ligands to keep in standardized summaries.
top_n_targets: Number of top targets per ligand to keep in standardized summaries.
species: Species for default NicheNet prior model loading.
lr_network: Optional ligand-receptor prior model or path to an .rds file.
ligand_target_matrix: Optional ligand-target prior model or path to an .rds file.
weighted_networks: Optional weighted network list or path to an .rds file.
cutoff_visualization: Cutoff passed to nichenetr::prepare_ligand_target_visualization().
lfc_cutoff: Log fold change cutoff for DE analysis in "aggregate" and "aggregate_cluster_de" modes.
use_sender_agnostic_background: Whether to use all sender cell types when sender = "all".
backend: Backend used for post-processing aggregation. Upstream NicheNet inference is unchanged.
verbose: Whether to print the message. Default is TRUE.
srt: Deprecated alias for object; supply exactly one of the two. It will be removed in scop 1.0.0.
merged_table_file: Optional path to a CSV file for exporting a temporary ligand-receptor/activity/target merged table. The file is not stored in the result bundle. Existing files and missing parent directories are rejected.

Value

A Seurat object with standardized NicheNet results stored in srt@tools[["Nichenetr"]].

Details

In the exported table, a ligand's predicted targets are repeated for each candidate receptor from the LR table. This is a ligand-level display of the existing results; it does not establish receptor-mediated targets or sender-specific target effects.

Examples

if (FALSE) { # \dontrun{
srt <- RunNichenetr(
  object = srt,
  group.by = "celltype",
  receiver = "Receiver",
  condition.by = "condition",
  condition_oi = "case",
  condition_reference = "control",
  merged_table_file = "NicheNet_merged.csv"
)
} # }