NA heatmap visualisation for 2 groups
Produces a heatmap after reordring rows and columsn to highlight missing value patterns.
imageNA2( object, pcol, Rowv, Colv = TRUE, useGroupMean = FALSE, plot = TRUE, ... )
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)
|
Rowv |
Determines if and how the rows/features are
reordered. If missing (default), rows are reordered according to
|
Colv |
A |
useGroupMean |
Replace individual feature intensities by the group mean intensity. Default is FALSE. |
plot |
A |
... |
Additional arguments passed to |
Used for its side effect of plotting. Invisibly returns Rovw and Colv.
Laurent Gatto, Samuel Wieczorek and Thomas Burger
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)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.