Run CARD spatial deconvolution

Estimate spot-level cell-type proportions from a spatial Seurat object using a single-cell Seurat reference and the optional CARD/CARDspa backend.

Usage

RunCARD(
  srt,
  reference,
  reference_label,
  assay = NULL,
  reference_assay = NULL,
  layer = "counts",
  reference_layer = "counts",
  features = NULL,
  image = NULL,
  coord.cols = c("col", "row"),
  sample_varname = NULL,
  minCountGene = 100,
  minCountSpot = 5,
  ct_select = NULL,
  prefix = "CARD",
  tool_name = "CARD",
  store_results = TRUE,
  round_counts = TRUE,
  create_card_params = list(),
  card_deconvolution_params = list(),
  verbose = TRUE,
  ...
)

Arguments

srt: Spatial Seurat object used as the RCTD query.
reference: Reference Seurat object containing annotated single cells.
reference_label: Metadata column in reference with cell type labels.
assay: Assay used in srt. If NULL, the default assay is used.
reference_assay: Assay used in reference.
layer, reference_layer: Assay layers used for spatial and reference raw counts.
features: Features used for RCTD. If NULL, shared features are used.
image: Name of the Seurat spatial image used to recover coordinates when coord.cols are not available.
coord.cols: Metadata coordinate columns used when no image coordinate source is requested or available.
sample_varname: Optional metadata column in reference containing sample labels. When NULL, all reference cells are assigned to one sample.
minCountGene, minCountSpot: Filtering parameters passed to CARD::createCARDObject() or CARDspa::createCARDObject() when supported.
ct_select: Optional cell types to keep in CARD.
prefix: Prefix for metadata columns.
tool_name: Name used to store detailed results in srt@tools.
store_results: Whether to store detailed RCTD results in srt@tools.
round_counts: Whether to round non-integer counts to the nearest integer before passing data to spacexr. RCTD requires integer count matrices; this defaults to TRUE so bundled example data with scaled non-integer reference counts can run directly.
create_card_params: Additional parameters passed to createCARDObject().
card_deconvolution_params: Additional parameters passed to CARD_deconvolution().
verbose: Whether to print the message. Default is TRUE.
...: Additional parameters passed to the RCTD run step.

Value

A Seurat object with CARD proportion columns in metadata and dominant cell type summaries. When store_results = TRUE, detailed results are stored in srt@tools[[tool_name]].

Examples

data(visium_human_pancreas_sub)
spatial <- visium_human_pancreas_sub
card_weights <- data.frame(
  CARD_prop_Ductal = seq(0.70, 0.20, length.out = ncol(spatial)),
  CARD_prop_Endocrine = seq(0.20, 0.70, length.out = ncol(spatial)),
  CARD_prop_Stromal = 0.10,
  row.names = colnames(spatial)
)
card_weights <- card_weights / rowSums(card_weights)
spatial <- Seurat::AddMetaData(spatial, card_weights)
spatial$CARD_dominant_type <- sub(
  "^CARD_prop_",
  "",
  colnames(card_weights)[max.col(card_weights)]
)
spatial$CARD_max_prop <- apply(card_weights, 1, max)

SpatialSpotPlot(
  spatial,
  group.by = "CARD_dominant_type",
  overlay_image = FALSE,
  coord.cols = c("x", "y")
)

if (requireNamespace("scatterpie", quietly = TRUE)) {
  SpatialSpotPlot(
    spatial,
    group.by = "CARD_dominant_type",
    plot_type = "pie",
    overlay_image = FALSE,
    coord.cols = c("x", "y")
  )
}


if (
  (isTRUE(check_r("CARD", verbose = FALSE)) ||
    isTRUE(check_r("CARDspa", verbose = FALSE)))
) {
data(pancreas_sub)
features_use <- head(intersect(rownames(spatial), rownames(pancreas_sub)), 300)
spatial <- RunCARD(
  spatial,
  reference = pancreas_sub,
  reference_label = "CellType",
  assay = "Spatial",
  reference_assay = "RNA",
  features = features_use,
  verbose = FALSE
)
}
#> Error in check_r("CARD", verbose = FALSE): could not find function "check_r"