workflowClusters {clusterExperiment} | R Documentation

## Methods for workflow clusters

### Description

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.

### Usage

    ## 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)

### Arguments

`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"

### Value

`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.

### Examples

    data(simData)

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

    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)

[Package clusterExperiment version 2.7.2 Index]