plotBarplot: Barplot of 1 or 2 clusterings
In clusterExperiment: Compare Clusterings for Single-Cell Sequencing

Description Usage Arguments Details Value Author(s) Examples

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 `ClusterExperiment` object.
`whichClusters`	argument that can be either numeric or character vector indicating the clusterings to be used. See details of `getClusterIndex`.
`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 `plotBarplot` arguments passed either to the method of `plotBarplot` for matrices or ultimately to `barplot`.
`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, `xNames` and `legNames` refer to the same clustering. See details.
`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 `clusters`, will be given this color (meant for samples not assigned to cluster).
`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

#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)