Seurat (version 4.0.1)

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

Description

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

Usage

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

Arguments

object

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

group.by

Name of one or more metadata columns to group (color) cells by (for example, orig.ident); pass 'ident' to group by identity class

alpha

Controls opacity of spots. Provide as a vector specifying the min and max

combine

Combine plots into a single patchworked ggplot object. If FALSE, return a list of ggplot objects

feature

Feature to visualize

slot

Which slot to pull expression data from?

Value

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

Examples

# NOT RUN {
LinkedDimPlot(seurat.object)
LinkedFeaturePlot(seurat.object, feature = 'Hpca')
# }
# NOT RUN {
# }