ClusterExperiment-methods {clusterExperiment} | R Documentation |
This is a collection of helper methods for the ClusterExperiment class.
## 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, ...)
x, object |
a ClusterExperiment object. |
..., i, j, drop |
Forwarded to the
|
value |
The value to be substituted in the corresponding slot. See the
slot descriptions in |
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 |
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.
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.