BoxplotsFromCounts: Produce notched boxplots from count data

In ATpoint/misterplotR: Functions for plotting and clustering of count data

Description

This minimal function accepts a count matrix (columns=samples, rows=regions/genes) and then uses ggplot2 to produce notched boxplots.

Usage

BoxplotsFromCounts(
  InputData,
  ScaleByQuantile = NULL,
  Box.title = NULL,
  Box.color = "darkgoldenrod2",
  Box.ylab = "",
  Box.axislabsize = 25,
  Box.titlesize = 25,
  add.NumberElements = TRUE,
  Return.Plot = FALSE
)

Arguments

InputData	a matrix or dataframe with the count data
ScaleByQuantile	a numeric vector with two elements that define the lower and upper quantile which will be used to winsorize the data in order to limit infuence of outliers on the plot.
Box.title	the title of the boxplots
Box.color	the color to fill the boxes with
Box.ylab	the y-axis description
Box.axislabsize	the fontsize of the axis labels
Box.titlesize	the fontsize of the title
add.NumberElements	logical, whether to add the number of rows of the count matrix to the end of the plot title like <PlotTitle (1000 elements)>
Return.Plot	logical, whether to return the ggplot2 object to be saved as a variable

Details

Not much to say here. The function accepts the counts "as-is" so any normalization or averaging of samples has to be done externally.

Author(s)

Alexander Toenges

Examples

cts <- sapply(seq(1,10), function(x) rnorm(1000,100))
colnames(cts) <- paste0("sample", seq(1,10))
PlotSaved <- BoxplotsFromCounts(InputData = cts, ScaleByQuantile = c(.01, .99), Box.title = "The main title", Return.Plot = TRUE)

ATpoint/misterplotR documentation built on Feb. 15, 2020, 12:17 a.m.