Run cell2location spatial deconvolution

Estimate cell-type abundances and proportions in spatial transcriptomics data using cell2location.

Usage

RunCell2location(
  object,
  result_dir,
  reference = NULL,
  reference_label = "celltype",
  reference_signatures = NULL,
  assay = NULL,
  reference_assay = NULL,
  layer = "counts",
  reference_layer = "counts",
  features = NULL,
  spatial_batch = NULL,
  reference_batch = NULL,
  reference_covariates = NULL,
  min_cells = 5L,
  N_cells_per_location = 30,
  detection_alpha = 20,
  gene_filter_params = list(cell_count_cutoff = 5, cell_percentage_cutoff2 = 0.03,
    nonz_mean_cutoff = 1.12),
  reference_train_params = list(max_epochs = 250L, batch_size = 2500L, train_size = 1, lr
    = 0.002, accelerator = "auto", device = "auto"),
  spatial_train_params = list(max_epochs = 30000L, batch_size = NULL, train_size = 1,
    accelerator = "auto", device = "auto"),
  reference_posterior_params = list(num_samples = 1000L, batch_size = 2500L),
  spatial_posterior_params = list(batch_size = 2500L),
  envname = NULL,
  resume = TRUE,
  overwrite = FALSE,
  prefix = "Cell2location",
  tool_name = "Cell2location",
  store_results = TRUE,
  verbose = TRUE,
  srt = NULL
)

Arguments

object: Spatial Seurat object containing raw counts.
result_dir: Directory used to persist inputs, models, posterior results, tables, logs, and the run manifest.
reference: Optional single-cell Seurat reference. Required when reference_signatures is NULL.
reference_label: Metadata column in reference containing cell types.
reference_signatures: Optional gene-by-cell-type numeric matrix, data.frame, or CSV file. When supplied, reference-model training is skipped.
assay, reference_assay: Assays containing spatial and reference counts.
layer, reference_layer: Raw-count layers.
features: Optional features to consider before shared non-zero genes are selected.
spatial_batch, reference_batch: Optional metadata columns describing spatial and reference batches.
reference_covariates: Optional categorical reference metadata columns used to model technical effects.
min_cells: Minimum number of reference cells retained per cell type.
N_cells_per_location: Expected average number of cells per spatial location.
detection_alpha: Prior controlling within-batch variation in RNA detection sensitivity.
gene_filter_params: Named arguments passed to cell2location.utils.filtering.filter_genes().
reference_train_params, spatial_train_params: Named arguments passed to the reference and spatial model train() methods.
reference_posterior_params: Named sampling arguments used when exporting reference signatures.
spatial_posterior_params: Named sampling arguments used when exporting the spatial q05 posterior.
envname: Name of the shared SCOP Python environment.
resume: Reuse completed stages only when their manifest matches the current inputs and parameters.
overwrite: Permit replacement of incompatible existing artifacts.
prefix: Prefix used for abundance/proportion metadata columns.
tool_name: Name of the srt@tools result entry.
store_results: Whether to store detailed result matrices and paths in object@tools.
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.

Value

A Seurat object with cell2location abundance, proportion, dominant cell type, and maximum-proportion metadata.

Details

Requires raw spatial counts and an annotated single-cell reference or gene-by-cell-type signatures with matching gene identifiers.

Usage

Arguments

Value

Details

See also