Description Usage Arguments Details Value Warning See Also Examples
Creating heatmaps with annotated columns
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | annHeatmap(x, ...)
## Default S3 method:
annHeatmap(
x,
annotation,
dendrogram = list(clustfun = hclust, distfun = dist, Col = list(status = "yes"), Row
= list(status = "hidden")),
cluster = NULL,
labels = NULL,
legend = TRUE,
...
)
## S3 method for class 'ExpressionSet'
annHeatmap(x, ...)
|
x |
either a numerical matrix with the data for the central heatmap
(for the default method) or an object of class |
... |
extra options passed to |
annotation |
a data frame containing the annotation for the columns of
|
dendrogram |
a list controlling the options for row- and column
dendrogram, see |
cluster |
a list controlling the options for clustering rows and
columns of |
labels |
a list controlling the row- and column labels as well as their
location and size, see |
legend |
either a logical value, indicating whether to draw a legend at
the default location determined by the function, or one of the sides of the
plot (1-4), see |
These functions generate an object representing the heatmap; in order to
produce graphical output, you have to invoke the plot
method, see
Examples.
An object of class annHeatmap
These are currently simple convenience functions that
allow quick plotting, but little control over the finer details. This may
change in the future, but for now, if you want to do anything fancy, you
should invoke annHeatmap2
directly.
1 2 3 4 5 6 7 8 9 10 11 12 | ## Default method
set.seed(219)
mat = matrix(rnorm(100), ncol=5)
ann = data.frame(Class=c("A","A","B","A","B"))
map1 = annHeatmap(mat, ann)
plot(map1)
## Expression set
require(Biobase)
data(sample.ExpressionSet)
map2 = annHeatmap(sample.ExpressionSet)
plot(map2)
|
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