ClusterExperiment-methods {clusterExperiment}R Documentation

Helper methods for the ClusterExperiment class

Description

This is a collection of helper methods for the ClusterExperiment class.

Usage

## S4 method for signature 'ClusterExperiment,ANY,character,ANY'
x[i, j, ..., drop = TRUE]

## S4 method for signature 'ClusterExperiment,ANY,logical,ANY'
x[i, j, ..., drop = TRUE]

## S4 method for signature 'ClusterExperiment,ANY,numeric,ANY'
x[i, j, ..., drop = TRUE]

## S4 method for signature 'ClusterExperiment'
show(object)

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

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

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

## S4 replacement method for signature 'ClusterExperiment,'function''
transformation(object) <- value

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

## S4 method for signature 'ClusterExperiment'
nClusters(x, ignoreUnassigned = TRUE)

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

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

## S4 method for signature 'ClusterExperiment,missing'
clusterMatrix(x, whichClusters)

## S4 method for signature 'ClusterExperiment,numeric'
clusterMatrix(x, whichClusters)

## S4 method for signature 'ClusterExperiment,character'
clusterMatrix(x, whichClusters)

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

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

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

## S4 replacement method for signature 'ClusterExperiment,numeric'
primaryClusterIndex(object) <- value

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

## S4 replacement method for signature 'ClusterExperiment,matrix'
coClustering(object) <- value

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

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

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

## S4 replacement method for signature 'ClusterExperiment,character'
clusterLabels(object) <- value

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

## S4 replacement method for signature 'ClusterExperiment,list'
clusterLegend(object) <- value

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

## S4 replacement method for signature 'ClusterExperiment,numeric'
orderSamples(object) <- value

## S4 replacement method for signature 'ClusterExperiment,character'
clusterTypes(object) <- value

## S4 method for signature 'ClusterExperiment,character'
tableClusters(x, whichClusters, ...)

## S4 method for signature 'ClusterExperiment,missing'
tableClusters(x, whichClusters, ...)

## S4 method for signature 'ClusterExperiment,numeric'
tableClusters(x, whichClusters, ...)

Arguments

x, object

a ClusterExperiment object.

..., i, j, drop

Forwarded to the SingleCellExperiment method.

value

The value to be substituted in the corresponding slot. See the slot descriptions in ClusterExperiment for details on what objects may be passed to these functions.

ignoreUnassigned

logical. If true, ignore the clusters with -1 or -2 assignments in calculating the number of clusters per clustering.

whichClusters

optional argument that can be either numeric or character value. If numeric, gives the indices of the clusterMatrix to return; this can also be used to defined an ordering for the clusterings. whichClusters can be a character value identifying the clusterTypes to be used, or if not matching clusterTypes then clusterLabels; alternatively whichClusters can be either 'all' or 'workflow' to indicate choosing all clusters or choosing all workflowClusters. If missing, the entire matrix of all clusterings is returned.

Details

Note that when subsetting the data, the dendrogram information and the co-clustering matrix are lost.

Note that redefining the transformation function via transformation(x)<- will check the validity of the transformation on the data assay. If the assay is large, this may be time consuming. Consider using a call to ClusterExperiment, which has the option as to whether to check the validity of the transformation.

Value

clusterMatrixNamed returns a matrix with cluster labels.

primaryClusterNamed returns the primary cluster (using cluster labels).

transformation prints the function used to transform the data prior to clustering.

nClusterings returns the number of clusterings (i.e., ncol of clusterMatrix).

nClusters returns the number of clusters per clustering

nFeatures returns the number of features (same as 'nrow').

nSamples returns the number of samples (same as 'ncol').

clusterMatrix returns the matrix with all the clusterings.

clusterMatrix returns the matrix with all the clusterings.

clusterMatrix returns the matrix with all the clusterings.

primaryCluster returns the primary clustering (as numeric).

primaryClusterIndex returns/sets the primary clustering index (i.e., which column of clusterMatrix corresponds to the primary clustering).

dendroClusterIndex returns/sets the clustering index of the clusters used to create dendrogram (i.e., which column of clusterMatrix corresponds to the clustering).

coClustering returns/sets the co-clustering matrix.

clusterTypes returns/sets the clusterTypes slot.

clusteringInfo returns the clusterInfo slot.

clusterLabels returns/sets the column names of the clusterMatrix slot.

clusterLegend returns/sets the clusterLegend slot.

orderSamples returns/sets the orderSamples slot.

[Package clusterExperiment version 2.0.2 Index]