Run RCTD spatial deconvolution

Estimate spot-level cell type proportions from a spatial Seurat object using a single-cell Seurat reference and spacexr RCTD.

Usage

RunRCTD(
  srt,
  reference,
  reference_label = "celltype",
  assay = NULL,
  reference_assay = NULL,
  layer = "counts",
  reference_layer = "counts",
  features = NULL,
  image = NULL,
  coord.cols = c("x", "y"),
  rctd_mode = c("full", "multi", "doublet"),
  max_cores = 1,
  min_cells = 25,
  prefix = "RCTD",
  store_results = TRUE,
  round_counts = TRUE,
  create_rctd_params = list(),
  run_rctd_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.
rctd_mode: RCTD mode passed to spacexr. "full" is the default for Visium spot deconvolution.
max_cores: Number of cores passed to spacexr.
min_cells: Minimum number of reference cells required for each cell type. Old spacexr RCTD requires at least 25 cells per type.
prefix: Prefix for metadata columns.
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_rctd_params: Additional parameters passed to spacexr::createRctd() or spacexr::create.RCTD().
run_rctd_params: Additional parameters passed to spacexr::runRctd() or spacexr::run.RCTD().
verbose: Whether to print the message. Default is TRUE.
...: Additional parameters passed to the RCTD run step.

Value

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

Examples

if (FALSE) { # \dontrun{
library(scop)

data(visium_human_pancreas_sub)
data(panc8_sub)

drop_celltypes <- c(
  "epsilon",
  "macrophage",
  "mast",
  "quiescent-stellate",
  "schwann"
)

panc8_rctd <- subset(
  panc8_sub,
  subset = !celltype %in% drop_celltypes
)

table(panc8_sub$celltype)
table(panc8_rctd$celltype)

spatial <- RunRCTD(
  srt = visium_human_pancreas_sub,
  reference = panc8_rctd,
  reference_label = "celltype",
  assay = "Spatial",
  reference_assay = "RNA",
  layer = "counts",
  reference_layer = "counts",
  rctd_mode = "full",
  max_cores = 1,
  prefix = "RCTD"
)

rctd_cols <- grep("^RCTD_prop_", colnames(spatial@meta.data), value = TRUE)
head(spatial@meta.data[, c("RCTD_dominant_type", "RCTD_max_prop", rctd_cols[1:3])])

SpatialSpotPlot(
  spatial,
  group.by = "RCTD_dominant_type",
  theme_use = "theme_scop"
)

SpatialSpotPlot(
  spatial,
  group.by = rctd_cols[1:min(4, length(rctd_cols))],
  palette = "Spectral",
  theme_use = "theme_scop"
)

SpatialSpotPlot(
  spatial,
  group.by = "RCTD_dominant_type",
  plot_type = "pie",
  pie.radius.scale = 0.45,
  theme_use = "theme_scop"
)
} # }