clusterVisualHclust-class {goCluster} | R Documentation |
This class can be used in order to visualize annotation terms that have been found as overrepresented in clusters identified with a hierarchical clustering. These annotation terms are displayed alongside the hierarchical clustering result.
The class provides a wrapper around the
prepareAxis
-function. Please read the corresponding
documentation for further details.
prepared
:"list"
, the number of
vectors stored in this list corresponds to the number of
annotations analyzed. Each vector contains the same number of
items as there are nodes in the tree of the clustering (number of
genes - 1). The order of appearence corresponds to the ordering of
the dendrogram so that the sorted dendrogram and the annotation
terms can be put alongside each other.
Additional slots are described in the documentation of the
clusterVisual-class
and clusterModule-class
.
Class "clusterVisual"
, directly.
Class "clusterModule"
, by class "clusterVisual"
.
signature(object = "clusterVisualHclust")
:
interactive setup of the class. There are no options that you can
set on this class.signature(object = "clusterVisualHclust")
:
returns the configuration of the object as a list. Since there are
no options to this class, this is always an empty list. signature(object = "clusterVisualHclust")
:
non-interactive setup of the class. Not necessary since this class
has no options.signature(object = "clusterVisualHclust")
:
prepares the selected annotation terms for the visualization. signature(object = "clusterVisualHclust")
:
resets the results of this class so that the analysis can be run
again. signature(object = "clusterVisualHclust")
:
generates the actual graphic for this object. signature(x = "clusterVisualHclust")
: prints
generic information about the object. Gunnar Wrobel, work@gunnarwrobel.de, http://www.gunnarwrobel.de.
prepareAxis
,
goCluster-class
,
clusterModule-class
,
clusterVisual-class
set.seed(1000) data(benomylsetupsmall) benomylsetupsmall$classalgo <- "clusterAlgorithmHclust" benomylsetupsmall$algo$method <- "complete" benomylsetupsmall$algo$distance <- "euclidean" benomylsetupsmall$classvisu <- "clusterVisualHclust" a <- new("goCluster") execute(a) <- benomylsetupsmall if(interactive()){ ## This example can only be run in an interactive mode ## This plot shows only one labeled region since the ## loaded dataset has been reduced to only 100 genes. ## Try the same with the full dataset display(a, selection = 1) }