GenePlot: Scatter plot of single cell data

In mayer-lab/SeuratForMayer2018: Seurat : R Toolkit for Single Cell Genomics

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

mayer-lab/SeuratForMayer2018 documentation built on May 25, 2019, 9:34 p.m.