subBoxplot: boxplot with data points

In peterawe/CMScaller: CMScaller: an R package for consensus molecular subtyping of colorectal cancer pre-clinical models

Description

Boxplot with data points and labeled outliers.

Usage

subBoxplot(
  y,
  x,
  labels = NULL,
  keepN = TRUE,
  classCol = getOption("subClassCol"),
  points = FALSE,
  width = 20,
  showOutliers = FALSE,
  ...
)

Arguments

y	a numeric vector.
x	a factor, length(x)==length(y).
labels	a character vector, if NULL, names(y) is used.
keepN	logical or numeric indicating which samples to include.
classCol	a character vector specifying class colors.
points	logical indicating whether points are to be added to boxes.
width	numeric to adjust point stacking - increase to reduce width.
showOutliers	logical indicating whether outliers are highlighted.
...	additional arguments to be passed to graphics::boxplot.

Value

a boxplot

Note

For data points, y-values are grouped and averaged - not exact!

Examples

isCMS4 <- rownames(crcTCGAsubset) %in%
    templates.CMS$probe[templates.CMS$class == 'CMS4']
y <- colSums(Biobase::exprs(crcTCGAsubset)[isCMS4,])
x <- crcTCGAsubset$CMS
subBoxplot(y, x, ylab = expression(sum(log2(RSEM))), main = 'CMS4 genes',
     keepN = which(x != "CMS1"), notch = TRUE)

peterawe/CMScaller documentation built on June 13, 2020, 4:49 a.m.