plotClustersWorkflow: A plot of clusterings specific for clusterMany and workflow...

In clusterExperiment: Compare Clusterings for Single-Cell Sequencing

Description

A realization of plotClusters call specific to separating out the results of clusterMany and other clustering results.

Usage

## S4 method for signature 'ClusterExperiment'
plotClustersWorkflow(
  object,
  whichClusters = c("mergeClusters", "makeConsensus"),
  whichClusterMany = NULL,
  nBlankLines = ceiling(nClusterings(object) * 0.05),
  existingColors = c("ignore", "all", "highlightOnly"),
  nSizeResult = ceiling(nClusterings(object) * 0.02),
  clusterLabels = TRUE,
  clusterManyLabels = TRUE,
  sortBy = c("highlighted", "clusterMany"),
  highlightOnTop = TRUE,
  ...
)

Arguments

object	A ClusterExperiment object on which clusterMany has been run
whichClusters	which clusterings to "highlight", i.e draw separately from the bulk of the plot, see argument whichClusters of getClusterIndex for description of format allowed.
whichClusterMany	indicate which clusterings to plot in the bulk of the plot, see argument whichClusters of getClusterIndex for description of format allowed.
nBlankLines	the number of blank (i.e. white) rows to add between the clusterMany clusterings and the highlighted clusterings.
existingColors	one of "ignore","all","highlightOnly". Whether the plot should use the stored colors in the ClusterExperiment object given. "highlightOnly" means only the highlighted clusters will use the stored colors, not the clusterMany clusterings.
nSizeResult	the number of rows each highlighted clustering should take up. Increasing the number increases the thickness of the rectangles representing the highlighted clusterings.
clusterLabels	either logical, indicating whether to plot the labels for the clusterings identified to be highlighted in the whichClusters argument, or a character vector of labels to use.
clusterManyLabels	either logical, indicating whether to plot the labels for the clusterings from clusterMany identified in the whichClusterMany, or a character vector of labels to use.
sortBy	how to align the clusters. If "highlighted" then the highlighted clusters indicated in the argument whichClusters are first in the alignment done by plotClusters. If "clusterMany", then the clusterMany results are first in the alignment. (Note this does not determine where they will be plotted, but how they are ordered in the aligning step done by plotClusters)
highlightOnTop	logical. Whether the highlighted clusters should be plotted on the top of clusterMany results or underneath.
...	arguments passed to the matrix version of plotClusters

Details

This plot is solely intended to make it easier to use the plotClusters visualization when there are a large number of clusterings from a call to clusterMany. This plot separates out the clusterMany results from a designated clustering of interest, as indicated by the whichClusters argument (by default clusterings from a call to makeConsensus or mergeClusters). In addition the highlighted clusters are made bigger so that they can be easily seen.

Value

A plot is produced, nothing is returned.

See Also

plotClusters, clusterMany

Examples

#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)
cl <- makeConsensus(cl, proportion=0.7)
plotClustersWorkflow(cl)

clusterExperiment documentation built on Feb. 11, 2021, 2 a.m.