Produces a heatmap after reordring rows and columsn to highlight missing value patterns.
imageNA2(
object,
pcol,
Rowv,
Colv = TRUE,
useGroupMean = FALSE,
plot = TRUE,
...
)
An instance of class MSnSet
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.
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.
A logical
that determines if columns/samples
are reordered. Default is TRUE
.
Replace individual feature intensities by the group mean intensity. Default is FALSE.
A logical
specifying of an image should be
produced. Default is TRUE
.
Additional arguments passed to image
.
Used for its side effect of plotting. Invisibly returns Rovw and Colv.
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)