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Spatial neighborhood plot

Source: R/RunSpatialNeighborhood.R
SpatialNeighborhoodPlot.Rd

Visualize results produced by RunSpatialNeighborhood() using spatial, statistical, and network plotting conventions.

Usage

SpatialNeighborhoodPlot(
  object,
  method = NULL,
  plot_type = c("heatmap", "network", "stat", "spatial"),
  comparison = NULL,
  condition = NULL,
  value = c("estimate", "fraction", "count"),
  FDR_threshold = 0.05,
  top_n = 30,
  layout = c("fr", "nicely", "kk", "circle", "mds"),
  edge_size = c(0.4, 2),
  cols.enriched = "#d7301f",
  cols.depleted = "#2b8cbe",
  cols.ns = "grey75",
  pair = NULL,
  image = NULL,
  overlay_image = TRUE,
  coord.cols = c("col", "row"),
  split.by = NULL,
  palette = "RdBu",
  palcolor = NULL,
  legend.position = "right",
  legend.direction = "vertical",
  legend.title = NULL,
  theme_use = "theme_scop",
  theme_args = list(),
  combine = TRUE,
  nrow = NULL,
  ncol = NULL,
  byrow = TRUE,
  seed = 11,
  verbose = TRUE,
  ...,
  image.scale = c("lowres", "hires"),
  srt = NULL,
  sample = NULL
)

Arguments

object

A Seurat object.

method

Stored neighborhood method to plot. If NULL, the active method is used.

plot_type

Plot type. One of "heatmap", "network", "stat", or "spatial".

comparison, condition

Optional filters for stored result tables. Spatial plots support condition using saved source-cell conditions, but reject comparison; use statistical plots for differential comparisons.

value

Column used as the plotted effect value. Spatial plots default to and only support "count": saved observed outgoing edges to the target type, not a spicyR effect. Other plot types retain the "estimate" default.

sample

Optional single sample ID for non-spatial plots. Results from multiple samples require explicit selection; no samples are aggregated. Use comparison and condition to resolve other repeated label pairs.

FDR_threshold

FDR cutoff used to mark significant pairs.

top_n

Number of pairs to show for network and statistic plots.

layout

Network layout.

edge_size

Network edge size range.

cols.enriched, cols.depleted, cols.ns

Colors for direction categories.

pair

Pair to visualize for plot_type = "spatial", either "from|to" or a length-2 character vector. Names must belong to the saved analysis and its from/to scope. Evaluated source cells without matching edges have zero counts; other cells have NA. Subsetting the object does not recompute saved counts. Valid empty edge results require an explicit pair; incomplete old results require rerunning.

image

Name of the Seurat spatial image. Required when multiple images are present; a single image is selected automatically when NULL.

overlay_image

Whether to draw the selected spatial image for plot_type = "spatial".

coord.cols

Metadata coordinate columns used when no Seurat image coordinates are available.

split.by

Optional metadata column identifying conditions for differential neighborhood statistics.

palette, palcolor

Palette name (thisplot::show_palettes) or custom colors.

legend.position, legend.direction, legend.title

Legend placement ("none", "left", "right", "bottom", "top"), direction, and title. legend.title = NULL uses the group name.

theme_use

Theme name or function.

theme_args

Theme name or function, plus extra theme arguments.

combine, nrow, ncol, byrow

Combine plots with patchwork. combine = FALSE returns a list of ggplots.

seed

Random seed used by layouts and jittered plot layers.

verbose

Whether to print the message. Default is TRUE.

...

Additional arguments passed to the selected backend.

image.scale

Image scale factor matching the raster stored in the selected image. Use "hires" for a hires raster; do not modify Seurat scale-factor slots.

srt

Deprecated alias for object; supply exactly one of the two. It will be removed in scop 1.0.0.

Value

A ggplot, patchwork, or list of ggplot objects.

See also

RunSpatialNeighborhood()

Examples

data(visium_human_pancreas_sub)
spatial <- visium_human_pancreas_sub
spatial <- RunSpatialNeighborhood(
  spatial,
  group.by = "coda_label",
  coord.cols = c("x", "y"),
  k = 4,
  verbose = FALSE
)

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