clust.stats.plot: Plotting tSNE, PCA, UMAP, Diffmap and other dim reductions

In iCellR: Analyzing High-Throughput Single Cell Sequencing Data

Description

This function takes an object of class iCellR and creates QC plot.

Usage

clust.stats.plot(
  x = NULL,
  plot.type = "box.mito",
  conds.to.plot = NULL,
  cell.color = "slategray3",
  cell.size = 1,
  cell.transparency = 0.5,
  box.color = "red",
  box.line.col = "green",
  back.col = "white",
  notch = FALSE,
  interactive = TRUE,
  out.name = "plot"
)

Arguments

x	An object of class iCellR.
plot.type	Choose from "bar.cc", "pie.cc" , box.umi", "box.mito", "box.gene", default = "box.mito".
conds.to.plot	Choose the conditions you want to see in the plot, default = NULL (all conditions).
cell.color	Choose a color for points in the plot.
cell.size	A number for the size of the points in the plot, default = 1.
cell.transparency	Color transparency for points in "scatterplot" and "boxplot", default = 0.5.
box.color	A color for the boxes in the "boxplot", default = "red".
box.line.col	A color for the lines around the "boxplot", default = "green".
back.col	Background color, default = "white"
notch	Notch the box plots, default = FALSE.
interactive	If set to TRUE an interactive HTML file will be created, default = TRUE.
out.name	If "interactive" is set to TRUE, the out put name for HTML, default = "plot".

Value

An object of class iCellR.

iCellR documentation built on Oct. 9, 2021, 5:07 p.m.