Visualize spatial and clustering (dimensional reduction) data in a linked, interactive framework

LinkedDimPlot(
  object,
  dims = 1:2,
  reduction = NULL,
  image = NULL,
  image.scale = "lowres",
  group.by = NULL,
  alpha = c(0.1, 1),
  combine = TRUE
)

LinkedFeaturePlot(
  object,
  feature,
  dims = 1:2,
  reduction = NULL,
  image = NULL,
  image.scale = "lowres",
  slot = "data",
  alpha = c(0.1, 1),
  combine = TRUE
)

Arguments

object

A Seurat object

dims

Dimensions to plot, must be a two-length numeric vector specifying x- and y-dimensions

reduction

Which dimensionality reduction to use. If not specified, first searches for umap, then tsne, then pca

image

Name of the image to use in the plot

image.scale

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

group.by

Name of meta.data column to group the data by

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.

combine

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

feature

Feature to visualize

slot

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

Value

Returns final plots. If combine, plots are stiched together using CombinePlots; otherwise, returns a list of ggplot objects

Examples

if (FALSE) {
LinkedDimPlot(seurat.object)
LinkedFeaturePlot(seurat.object, feature = 'Hpca')
}