Seurat (version 2.3.4)

DotPlot: Dot plot visualization

Description

Intuitive way of visualizing how gene 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 of cells within a class (blue is high).

Usage

DotPlot(object, genes.plot, cols.use = c("lightgrey", "blue"),
  col.min = -2.5, col.max = 2.5, dot.min = 0, dot.scale = 6,
  scale.by = "radius", scale.min = NA, scale.max = NA, group.by,
  plot.legend = FALSE, do.return = FALSE, x.lab.rot = FALSE)

Arguments

object

Seurat object

genes.plot

Input vector of genes

cols.use

Colors to plot, can pass a single character giving the name of a palette from RColorBrewer::brewer.pal.info

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

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

group.by

Factor to group the cells by

plot.legend

plots the legends

do.return

Return ggplot2 object

x.lab.rot

Rotate x-axis labels

Value

default, no return, only graphical output. If do.return=TRUE, returns a ggplot2 object

See Also

RColorBrewer::brewer.pal.info

Examples

# NOT RUN {
cd_genes <- c("CD247", "CD3E", "CD9")
DotPlot(object = pbmc_small, genes.plot = cd_genes)

# }