workflowClusters: Methods for workflow clusters
In clusterExperiment: Compare Clusterings for Single-Cell Sequencing

Description Usage Arguments Value Examples

The main workflow of the package is made of clusterMany, makeConsensus, and mergeClusters. The clusterings from these functions (and not those obtained in a different way) can be obtained with the functions documented here.

## S4 method for signature 'ClusterExperiment'
workflowClusters(x, iteration = 0)

## S4 method for signature 'ClusterExperiment'
workflowClusterDetails(x)

## S4 method for signature 'ClusterExperiment'
workflowClusterTable(x)

## S4 method for signature 'ClusterExperiment'
setToCurrent(x, whichCluster, eraseOld = FALSE)

## S4 method for signature 'ClusterExperiment'
setToFinal(x, whichCluster, clusterLabel)

`x`	a `ClusterExperiment` object.
`iteration`	numeric. Which iteration of the workflow should be used.
`whichCluster`	argument that can be a single numeric or character value indicating the single clustering to be used. Giving values that result in more than one clustering will result in an error. See details of `getClusterIndex`.
`eraseOld`	logical. Only relevant if input `x` is of class `ClusterExperiment`. If TRUE, will erase existing workflow results (clusterMany as well as mergeClusters and makeConsensus). If FALSE, existing workflow results will have "`_i`" added to the clusterTypes value, where `i` is one more than the largest such existing workflow clusterTypes.
`clusterLabel`	optional string value to give to cluster set to be "final"

workflowClusters returns a matrix consisting of the appropriate columns of the clusterMatrix slot.

workflowClusterDetails returns a data.frame with some details on the clusterings, such as the type (e.g., 'clusterMany', 'makeConsensus') and iteration.

workflowClusterTable returns a table of how many of the clusterings belong to each of the following possible values: 'final', 'mergeClusters', 'makeConsensus' and 'clusterMany'.

setToCurrent returns a ClusterExperiment object where the indicated cluster of whichCluster has been set to the most current iteration in the workflow. Pre-existing clusters are appropriately updated.

setToFinal returns a ClusterExperiment object where the indicated cluster of whichCluster has clusterType set to "final". The primaryClusterIndex is also set to this cluster, and the clusterLabel, if given.

data(simData)

cl <- clusterMany(simData,nReducedDims=c(5,10,50),  reduceMethod="PCA",
clusterFunction="pam", ks=2:4, findBestK=c(FALSE), removeSil=TRUE,
subsample=FALSE, makeMissingDiss=TRUE)

clCommon <- makeConsensus(cl, whichClusters="workflow", proportion=0.7,
minSize=10)

clCommon <- makeDendrogram(clCommon)

clMerged <- mergeClusters(clCommon,mergeMethod="adjP", DEMethod="limma")

head(workflowClusters(clMerged))
workflowClusterDetails(clMerged)
workflowClusterTable(clMerged)