NA heatmap visualisation for 2 groups

Produces a heatmap after reordring rows and columsn to highlight missing value patterns.

Usage

imageNA2(
  object,
  pcol,
  Rowv,
  Colv = TRUE,
  useGroupMean = FALSE,
  plot = TRUE,
  ...
)

Arguments

object

An instance of class MSnSet

pcol

Either the name of a phenoData variable to be used to determine the group structure or a factor or any object that can be coerced as a factor of length equal to nrow(object). The resulting factor must have 2 levels. If missing (default) image(object) is called.

Rowv

Determines if and how the rows/features are reordered. If missing (default), rows are reordered according to order((nNA1 + 1)^2/(nNA2 + 1)), where NA1 and NA2 are the number of missing values in each group. Use a vector of numerics of feautre names to customise row order.

Colv

A logical that determines if columns/samples are reordered. Default is TRUE.

useGroupMean

Replace individual feature intensities by the group mean intensity. Default is FALSE.

plot

A logical specifying of an image should be produced. Default is TRUE.

...

Additional arguments passed to image.

Value

Used for its side effect of plotting. Invisibly returns Rovw and Colv.

Author

Laurent Gatto, Samuel Wieczorek and Thomas Burger

Examples

library("pRolocdata")
library("pRoloc")
data(dunkley2006)
pcol <- ifelse(dunkley2006$fraction <= 5, "A", "B")
nax <- makeNaData(dunkley2006, pNA = 0.10)
exprs(nax)[sample(nrow(nax), 30), pcol == "A"] <- NA
exprs(nax)[sample(nrow(nax), 50), pcol == "B"] <- NA
MSnbase:::imageNA2(nax, pcol)

MSnbase:::imageNA2(nax, pcol, useGroupMean = TRUE)

MSnbase:::imageNA2(nax, pcol, Colv = FALSE, useGroupMean = FALSE)

MSnbase:::imageNA2(nax, pcol, Colv = FALSE, useGroupMean = TRUE)