FeatureScatter: Scatter plot of single cell data

Description

Creates a scatter plot of two features (typically feature expression), across a set of single cells. Cells are colored by their identity class. Pearson correlation between the two features is displayed above the plot.

Usage

FeatureScatter(
  object,
  feature1,
  feature2,
  cells = NULL,
  shuffle = FALSE,
  seed = 1,
  group.by = NULL,
  split.by = NULL,
  cols = NULL,
  pt.size = 1,
  shape.by = NULL,
  span = NULL,
  smooth = FALSE,
  combine = TRUE,
  slot = "data",
  plot.cor = TRUE,
  ncol = NULL,
  raster = NULL,
  raster.dpi = c(512, 512),
  jitter = FALSE,
  log = FALSE
)

Value

A ggplot object

Arguments

object: Seurat object
feature1: First feature to plot. Typically feature expression but can also be metrics, PC scores, etc. - anything that can be retreived with FetchData
feature2: Second feature to plot.
cells: Cells to include on the scatter plot.
shuffle: Whether to randomly shuffle the order of points. This can be useful for crowded plots if points of interest are being buried. (default is FALSE)
seed: Sets the seed if randomly shuffling the order of points.
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
split.by: A factor in object metadata to split the feature plot by, pass 'ident' to split by cell identity'
cols: Colors to use for identity class plotting.
pt.size: Size of the points on the plot
shape.by: Ignored for now
span: Spline span in loess function call, if NULL, no spline added
smooth: Smooth the graph (similar to smoothScatter)
combine: Combine plots into a single patchworked
slot: Slot to pull data from, should be one of 'counts', 'data', or 'scale.data'
plot.cor: Display correlation in plot title
ncol: Number of columns if plotting multiple plots
raster: Convert points to raster format, default is NULL which will automatically use raster if the number of points plotted is greater than 100,000
raster.dpi: Pixel resolution for rasterized plots, passed to geom_scattermore(). Default is c(512, 512).
jitter: Jitter for easier visualization of crowded points (default is FALSE)
log: Plot features on the log scale (default is FALSE)

Examples

Run this code

data("pbmc_small")
FeatureScatter(object = pbmc_small, feature1 = 'CD9', feature2 = 'CD3E')

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