plotBarplot,ClusterExperiment-method | R Documentation |
Make a barplot of sample's assignments to clusters for single clustering, or cross comparison for two clusterings.
## S4 method for signature 'ClusterExperiment'
plotBarplot(object, whichClusters = "primary", labels = c("names", "ids"), ...)
## S4 method for signature 'vector'
plotBarplot(object, ...)
## S4 method for signature 'matrix'
plotBarplot(
object,
xNames = NULL,
legNames = NULL,
legend = ifelse(ncol(object) == 2, TRUE, FALSE),
xlab = NULL,
legend.title = NULL,
unassignedColor = "white",
missingColor = "grey",
colPalette = NULL,
...
)
object |
A matrix of with each column corresponding to a clustering and
each row a sample or a |
whichClusters |
argument that can be either numeric or character vector
indicating the clusterings to be used. See details of |
labels |
if object is a ClusterExperiment object, then labels defines whether the clusters will be identified by their names values in clusterLegend (labels="names", the default) or by their clusterIds value in clusterLegend (labels="ids"). |
... |
for |
xNames |
names for the clusters on x-axis (i.e. clustering given 1st). By default uses names of the 1st column of clusters matrix. See details. |
legNames |
names for the clusters dividing up the 1st clusters (will
appear in legend). By default uses names of the 2nd cluster of clusters
matrix. If only one clustering, |
legend |
whether to plot the legend |
xlab |
label for x-axis. By default or if equal NULL the column name of the 1st cluster of clusters matrix |
legend.title |
label for legend. By default or if equal NULL the column name of the 2st cluster of clusters matrix |
unassignedColor |
If “-1” in |
missingColor |
If “-2” in clusters, will be given this color (meant for samples that were missing from the clustering, mainly when comparing clusterings run on different sets of samples) |
colPalette |
a vector of colors used for the different clusters. See details. |
The first column of the cluster matrix will be on the x-axis and the second column (if present) will separate the groups of the first column.
All arguments of the matrix version can be passed to the
ClusterExperiment
version. As noted above, however, some arguments
have different interpretations.
If whichClusters = "workflow"
, then the most recent two
clusters of the workflow will be chosen where recent is based on the
following order (most recent first): final, mergeClusters, makeConsensus,
clusterMany.
xNames
, legNames
and colPalette
should all be
named vectors, with the names referring to the clusters they should match
to (for ClusterExperiment
objects, it is determined by the argument
labels
as to whether the names should match the cluster names or the
clusterIds). colPalette
and legNames
must be same length of
the number of clusters found in the second clustering, or if only a single
clustering, the same length as the number of clusters in that clustering.
A plot is produced, nothing is returned
Elizabeth Purdom
## Not run:
#clustering using pam: try using different dimensions of pca and different k
data(simData)
cl <- clusterMany(simData, nReducedDims=c(5, 10, 50), reduceMethod="PCA",
clusterFunction="pam", ks=2:4, findBestK=c(TRUE,FALSE),
removeSil=c(TRUE,FALSE), makeMissingDiss=TRUE)
plotBarplot(cl)
plotBarplot(cl,whichClusters=1:2)
## End(Not run)
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