FeatureScatter: Scatter plot of single cell data

In satijalab/seurat: Tools for Single Cell Genomics

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
)

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)

Value

A ggplot object

Examples

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

satijalab/seurat documentation built on May 11, 2024, 4:04 a.m.