DotPlot: Dot plot visualization

In Seurat: Tools for Single Cell Genomics

Dot plot visualization

Description

Intuitive way of visualizing how feature expression changes across different identity classes (clusters). The size of the dot encodes the percentage of cells within a class, while the color encodes the AverageExpression level across all cells within a class (blue is high).

Usage

DotPlot(
  object,
  features,
  assay = NULL,
  cols = c("lightgrey", "blue"),
  col.min = -2.5,
  col.max = 2.5,
  dot.min = 0,
  dot.scale = 6,
  idents = NULL,
  group.by = NULL,
  split.by = NULL,
  cluster.idents = FALSE,
  scale = TRUE,
  scale.by = "radius",
  scale.min = NA,
  scale.max = NA
)

Arguments

object	Seurat object
features	Input vector of features, or named list of feature vectors if feature-grouped panels are desired (replicates the functionality of the old SplitDotPlotGG)
assay	Name of assay to use, defaults to the active assay
cols	Colors to plot: the name of a palette from RColorBrewer::brewer.pal.info, a pair of colors defining a gradient, or 3+ colors defining multiple gradients (if split.by is set)
col.min	Minimum scaled average expression threshold (everything smaller will be set to this)
col.max	Maximum scaled average expression threshold (everything larger will be set to this)
dot.min	The fraction of cells at which to draw the smallest dot (default is 0). All cell groups with less than this expressing the given gene will have no dot drawn.
dot.scale	Scale the size of the points, similar to cex
idents	Identity classes to include in plot (default is all)
group.by	Factor to group the cells by
split.by	A factor in object metadata to split the plot by, pass 'ident' to split by cell identity' see FetchData for more details
cluster.idents	Whether to order identities by hierarchical clusters based on given features, default is FALSE
scale	Determine whether the data is scaled, TRUE for default
scale.by	Scale the size of the points by 'size' or by 'radius'
scale.min	Set lower limit for scaling, use NA for default
scale.max	Set upper limit for scaling, use NA for default

Value

A ggplot object

See Also

RColorBrewer::brewer.pal.info

Examples

data("pbmc_small")
cd_genes <- c("CD247", "CD3E", "CD9")
DotPlot(object = pbmc_small, features = cd_genes)
pbmc_small[['groups']] <- sample(x = c('g1', 'g2'), size = ncol(x = pbmc_small), replace = TRUE)
DotPlot(object = pbmc_small, features = cd_genes, split.by = 'groups')

Seurat documentation built on May 29, 2024, 4:20 a.m.