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Visualize spatial clustering and expression data.

Source: R/visualization.R, R/convenience.R
SpatialPlot.Rd

SpatialPlot plots a feature or discrete grouping (e.g. cluster assignments) as spots over the image that was collected. We also provide SpatialFeaturePlot and SpatialDimPlot as wrapper functions around SpatialPlot for a consistent naming framework.

Usage

SpatialPlot(
  object,
  group.by = NULL,
  features = NULL,
  images = NULL,
  cols = NULL,
  image.alpha = 1,
  image.scale = "lowres",
  crop = TRUE,
  slot = "data",
  keep.scale = "feature",
  min.cutoff = NA,
  max.cutoff = NA,
  cells.highlight = NULL,
  cols.highlight = c("#DE2D26", "grey50"),
  facet.highlight = FALSE,
  label = FALSE,
  label.size = 5,
  label.color = "white",
  label.box = TRUE,
  repel = FALSE,
  ncol = NULL,
  combine = TRUE,
  pt.size.factor = 1.6,
  alpha = c(1, 1),
  shape = 21,
  stroke = NA,
  stroke.alpha = NA,
  interactive = FALSE,
  do.identify = FALSE,
  identify.ident = NULL,
  do.hover = FALSE,
  information = NULL,
  plot_segmentations = FALSE
)

SpatialDimPlot(
  object,
  group.by = NULL,
  images = NULL,
  cols = NULL,
  crop = TRUE,
  cells.highlight = NULL,
  cols.highlight = c("#DE2D26", "grey50"),
  facet.highlight = FALSE,
  label = FALSE,
  label.size = 7,
  label.color = "white",
  repel = FALSE,
  ncol = NULL,
  combine = TRUE,
  pt.size.factor = 1.6,
  alpha = c(1, 1),
  image.alpha = 1,
  image.scale = "lowres",
  shape = 21,
  stroke = NA,
  stroke.alpha = NA,
  label.box = TRUE,
  interactive = FALSE,
  information = NULL,
  plot_segmentations = FALSE
)

SpatialFeaturePlot(
  object,
  features,
  images = NULL,
  crop = TRUE,
  slot = "data",
  keep.scale = "feature",
  min.cutoff = NA,
  max.cutoff = NA,
  ncol = NULL,
  combine = TRUE,
  pt.size.factor = 1.6,
  alpha = c(1, 1),
  image.alpha = 1,
  image.scale = "lowres",
  shape = 21,
  stroke = NA,
  stroke.alpha = NA,
  interactive = FALSE,
  information = NULL,
  plot_segmentations = FALSE
)

Arguments

object

A Seurat object

group.by

Name of meta.data column to group the data by

features

Name of the feature to visualize. Provide either group.by OR features, not both.

images

Name of the images to use in the plot(s)

cols

Vector of colors, each color corresponds to an identity class. This may also be a single character or numeric value corresponding to a palette as specified by brewer.pal.info. By default, ggplot2 assigns colors

image.alpha

Adjust the opacity of the background images. Set to 0 to remove.

image.scale

Choose the scale factor ("lowres"/"hires") to apply in order to matchthe plot with the specified `image` - defaults to "lowres"

crop

Crop the plot in to focus on points plotted. Set to FALSE to show entire background image.

slot

If plotting a feature, which data slot to pull from (counts, data, or scale.data)

keep.scale

How to handle the color scale across multiple plots. Options are:

  • “feature” (default; by row/feature scaling): The plots for each individual feature are scaled to the maximum expression of the feature across the conditions provided to split.by

  • “all” (universal scaling): The plots for all features and conditions are scaled to the maximum expression value for the feature with the highest overall expression

  • NULL (no scaling): Each individual plot is scaled to the maximum expression value of the feature in the condition provided to split.by; be aware setting NULL will result in color scales that are not comparable between plots

min.cutoff, max.cutoff

Vector of minimum and maximum cutoff values for each feature, may specify quantile in the form of 'q##' where '##' is the quantile (eg, 'q1', 'q10')

cells.highlight

A list of character or numeric vectors of cells to highlight. If only one group of cells desired, can simply pass a vector instead of a list. If set, colors selected cells to the color(s) in cols.highlight

cols.highlight

A vector of colors to highlight the cells as; ordered the same as the groups in cells.highlight; last color corresponds to unselected cells.

facet.highlight

When highlighting certain groups of cells, split each group into its own plot

label

Whether to label the clusters

label.size

Sets the size of the labels

label.color

Sets the color of the label text

label.box

Whether to put a box around the label text (geom_text vs geom_label)

repel

Repels the labels to prevent overlap

ncol

Number of columns if plotting multiple plots

combine

Combine plots into a single gg object; note that if TRUE; themeing will not work when plotting multiple features/groupings

pt.size.factor

Scale the size of the spots.

alpha

Controls opacity of spots. Provide as a vector specifying the min and max for SpatialFeaturePlot. For SpatialDimPlot, provide a single alpha value for each plot.

shape

Control the shape of the spots - same as the ggplot2 parameter. The default is 21, which plots circles - use 22 to plot squares.

stroke

Control the width of the border around the spots

stroke.alpha

Control the opacity of spot borders (when stroke is specified). Set to NA to use the same alpha as the fill.

interactive

Launch an interactive SpatialDimPlot or SpatialFeaturePlot session, see ISpatialDimPlot or ISpatialFeaturePlot for more details

do.identify, do.hover

DEPRECATED in favor of interactive

identify.ident

DEPRECATED

information

An optional dataframe or matrix of extra information to be displayed on hover

plot_segmentations

Define whether plot should plot centroids or segmentations

Value

If do.identify, either a vector of cells selected or the object with selected cells set to the value of identify.ident (if set). Else, if do.hover, a plotly object with interactive graphics. Else, a ggplot object

Examples

if (FALSE) { # \dontrun{
# For functionality analagous to FeaturePlot
SpatialPlot(seurat.object, features = "MS4A1")
SpatialFeaturePlot(seurat.object, features = "MS4A1")

# For functionality analagous to DimPlot
SpatialPlot(seurat.object, group.by = "clusters")
SpatialDimPlot(seurat.object, group.by = "clusters")
} # }