Plot spatial integration results — SpatialIntegrationPlot • scop

Visualize standardized results produced by RunSpatialIntegration().

Usage

SpatialIntegrationPlot(
  srt,
  method = NULL,
  plot_type = c("spatial", "embedding", "alignment", "composition"),
  group.by = NULL,
  sample.by = NULL,
  reduction = NULL,
  cluster_colname = NULL,
  coord.cols = c("col", "row"),
  use_aligned = FALSE,
  tool_name = "SpatialIntegration",
  combine = TRUE,
  palette = "Chinese",
  palcolor = NULL,
  theme_use = "theme_scop",
  theme_args = list(),
  ...
)

Arguments

srt: A Seurat object containing spatial integration results.
method: Stored integration method. If NULL, the active method stored in srt@tools[[tool_name]] is used.
plot_type: Plot type: "spatial", "embedding", "alignment", or "composition".
group.by: Metadata column used for coloring. Defaults to the stored spatial domain column.
sample.by: Metadata column used for facets or composition grouping. Defaults to the stored sample column.
reduction: Reduction used for embedding plots. Defaults to the stored integration reduction.
cluster_colname: Backward-compatible alias for group.by.
coord.cols: Metadata coordinate columns used when no image is available.
use_aligned: Whether spatial plots should use aligned coordinates when available.
tool_name: Name of the srt@tools entry created by RunSpatialIntegration().
combine: Whether to combine plots when delegated plotting returns a list.
palette: Color palette name. Available palettes can be found in thisplot::show_palettes. Default is "Chinese".
palcolor: Custom colors used to create a color palette. Default is NULL.
theme_use: Theme used. Can be a character string or a theme function. Default is "theme_scop".
theme_args: Other arguments passed to the theme_use. Default is list().
...: Additional arguments passed to SpatialSpotPlot() or CellDimPlot().

Value

A ggplot, patchwork object, or list of plots.

Examples

data(visium_human_pancreas_sub)
spatial <- visium_human_pancreas_sub
spatial$sample <- ifelse(spatial$y > stats::median(spatial$y), "slice_a", "slice_b")
spatial$SpatialIntegration_PRECAST_domain <- factor(
  paste0("domain_", (seq_len(ncol(spatial)) - 1) %% 3 + 1)
)
embedding <- cbind(
  SI_1 = as.numeric(scale(spatial$x)),
  SI_2 = as.numeric(scale(spatial$y))
)
rownames(embedding) <- colnames(spatial)
spatial[["SpatialIntegration_PRECAST"]] <- SeuratObject::CreateDimReducObject(
  embeddings = embedding,
  key = "SI_",
  assay = "Spatial"
)
spatial$SpatialIntegration_PRECAST_aligned_x <- spatial$x +
  ifelse(spatial$sample == "slice_b", -stats::median(spatial$x), 0)
spatial$SpatialIntegration_PRECAST_aligned_y <- spatial$y
integration_parameters <- list(
  method = "PRECAST",
  sample.by = "sample",
  assay = "Spatial",
  layer = "counts",
  coord.cols = c("x", "y"),
  reduction.name = "SpatialIntegration_PRECAST",
  cluster_colname = "SpatialIntegration_PRECAST_domain",
  aligned_coord_cols = c(
    "SpatialIntegration_PRECAST_aligned_x",
    "SpatialIntegration_PRECAST_aligned_y"
  )
)
spatial@tools$SpatialIntegration <- list(
  active_method = "PRECAST",
  methods = list(PRECAST = list(parameters = integration_parameters)),
  parameters = integration_parameters,
  samples = unique(spatial$sample),
  cells = colnames(spatial)
)

SpatialIntegrationPlot(
  spatial,
  plot_type = "spatial",
  overlay_image = FALSE,
  coord.cols = c("x", "y")
)

SpatialIntegrationPlot(spatial, plot_type = "embedding")

SpatialIntegrationPlot(spatial, plot_type = "alignment")

SpatialIntegrationPlot(spatial, plot_type = "composition")