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.