Seurat (version 2.1.0)

GenePlot: Scatter plot of single cell data

Description

Creates a scatter plot of two features (typically gene expression), across a set of single cells. Cells are colored by their identity class.

Usage

GenePlot(object, gene1, gene2, cell.ids = NULL, col.use = NULL,
  pch.use = 16, cex.use = 1.5, use.imputed = FALSE, use.scaled = FALSE,
  use.raw = FALSE, do.hover = FALSE, data.hover = "ident",
  do.identify = FALSE, dark.theme = FALSE, do.spline = FALSE,
  spline.span = 0.75, ...)

Arguments

object

Seurat object

gene1

First feature to plot. Typically gene expression but can also be metrics, PC scores, etc. - anything that can be retreived with FetchData

gene2

Second feature to plot.

cell.ids

Cells to include on the scatter plot.

col.use

Colors to use for identity class plotting.

pch.use

Pch argument for plotting

cex.use

Cex argument for plotting

use.imputed

Use imputed values for gene expression (Default is FALSE)

use.scaled

Use scaled data

use.raw

Use raw data

do.hover

Enable hovering over points to view information

data.hover

Data to add to the hover, pass a character vector of features to add. Defaults to cell name and ident. Pass 'NULL' to clear extra information.

do.identify

Opens a locator session to identify clusters of cells.

dark.theme

Use a dark theme for the plot

do.spline

Add a spline (currently hardwired to df=4, to be improved)

spline.span

spline span in loess function call

…

Additional arguments to be passed to plot.

Value

No return, only graphical output

Examples

# NOT RUN {
GenePlot(object = pbmc_small, gene1 = 'CD9', gene2 = 'CD3E')

# }