This method clusters subjects based on feature data using any one of seven available clustering algorithms. See Arguments below.
modCluster(object, top = 0, how = "hclust", onlyCluster = FALSE, ...)# S4 method for ExprsArray
modCluster(object, top = 0, how = "hclust",
onlyCluster = FALSE, ...)
An ExprsArray
object. The object containing the subject
data to cluster.
A numeric scalar or character vector. A numeric scalar indicates
the number of top features that should undergo feature selection. A character vector
indicates specifically which features by name should undergo feature selection.
Set top = 0
to include all features. A numeric vector can also be used
to indicate specific features by location, similar to a character vector.
A character string. The name of the function used to cluster. Select from "hclust", "kmeans", "agnes", "clara", "diana", "fanny", or "pam".
A logical scalar. Toggles whether to return a processed
cluster object or an updated ExprsArray
object.
Additional arguments to the cluster function and/or
other functions used for clustering (e.g., dist
and
cutree
).
Typically an ExprsArray
object with subject cluster assignments
added to the $cluster
column of the @anot
slot.
ExprsArray
: Method to compare ExprsArray
objects.
Note that this function will expect the argument k
to define the returned
number of clusters, except when how = "kmeans"
in which case this
function will expect the argument centers
instead.