Initiate the CSNObject object — initiate

Initiate the CSNObject object

initiate_object(object, ...)

# S4 method for class 'matrix'
initiate_object(object, regulators = character(0), targets = character(0), ...)

# S4 method for class 'Seurat'
initiate_object(
  object,
  celltype = NULL,
  celltype_by = NULL,
  filter_mode = c("variable", "celltype", "unfiltered"),
  filter_by = c("aggregate", "celltype"),
  rna_assay = "RNA",
  rna_min_pct = 0.1,
  rna_logfc_threshold = 0.25,
  rna_test_method = "wilcox",
  n_variable_genes = 2000,
  peak_assay = NULL,
  peak_min_pct = 0.05,
  peak_logfc_threshold = 0.1,
  peak_test_method = "LR",
  n_variable_peaks = "q5",
  regions = NULL,
  exclude_exons = TRUE,
  only_pos = TRUE,
  verbose = TRUE,
  p_value = 0.05,
  ...
)

# S4 method for class 'CSNObject'
initiate_object(object, ...)

Arguments

object: A Seurat object containing gene expression and/or chromatin accessibility data.
...: Additional arguments passed to marker detection functions.
regulators: Regulators to consider for CSN inference.
targets: Targets to consider for CSN inference.
celltype: Selected celltype(s) to analyze. If NULL, all cells will be used.
celltype_by: Column name in Seurat meta.data for cell type information. If NULL, all cells will be treated as one group.
filter_mode: Filter mode for identifying cell-type specific features.
filter_by: Character. When filter_mode is "variable", specify whether to calculate variable features using "aggregate" cells or by "celltype". Default is "aggregate".
rna_assay: A character vector indicating the name of the gene expression assay in the Seurat object.
rna_min_pct: Minimum percentage of cells expressing the gene in either population.
rna_logfc_threshold: Minimum log fold-change threshold for RNA data.
rna_test_method: Statistical test to use for gene markers identification.
n_variable_genes: Number of variable features to select when not comparing between groups.
peak_assay: A character vector indicating the name of the chromatin accessibility assay in the Seurat object. If NULL, only RNA-seq data will be processed.
peak_min_pct: Minimum percentage of cells expressing the peak in either population.
peak_logfc_threshold: Minimum log fold-change threshold for peak data.
peak_test_method: Statistical test to use for peak markers identification.
n_variable_peaks: Number of variable peaks to select ("q5" by default).
regions: Candidate regions to consider for binding site inference. If NULL, all peaks regions are considered. regions could be a GRanges object, or a data frame with three columns: chrom, start, end.
exclude_exons: Logical. Whether to consider exons for binding site inference.
only_pos: Only return positive markers.
verbose: Print progress messages.
p_value: Significance level threshold for filtering features (default: 0.05).

Value

CSNObject object.