HclustParam-class: Hierarchical clustering
In bluster: Clustering Algorithms for Bioconductor

Description Usage Arguments Details Value Author(s) See Also Examples

Run the base hclust function on a distance matrix within clusterRows.

HclustParam(
  metric = "euclidean",
  method = "complete",
  cut.fun = NULL,
  cut.dynamic = FALSE,
  cut.height = NULL,
  cut.number = NULL,
  ...
)

## S4 method for signature 'ANY,HclustParam'
clusterRows(x, BLUSPARAM, full = FALSE)

`metric`	String specifying the distance metric to use in `dist`.
`method`	String specifying the agglomeration method to use in `hclust`.
`cut.fun`	Function specifying the method to use to cut the dendrogram. The first argument of this function should be the output of `hclust`, and the return value should be an atomic vector specifying the cluster assignment for each observation. Defaults to `cutree` if `cut.dynamic=FALSE` and `cutreeDynamic` otherwise.
`cut.dynamic`	Logical scalar indicating whether a dynamic tree cut should be performed using the dynamicTreeCut package.
`cut.height`	Numeric scalar specifying the cut height to use for the tree cut when `cut.fun=NULL`. If `NULL`, defaults to half the tree height. Ignored if `cut.number` is set.
`cut.number`	Integer scalar specifying the number of clusters to generate from the tree cut when `cut.fun=NULL`.
`...`	Further arguments to pass to `cut.fun`, when `cut.dynamic=TRUE` or `cut.fun` is non-`NULL`.
`x`	A numeric matrix-like object where rows represent observations and columns represent variables.
`BLUSPARAM`	A HclustParam object.
`full`	Logical scalar indicating whether the hierarchical clustering statistics should be returned.

To modify an existing HclustParam object x, users can simply call x[[i]] or x[[i]] <- value where i is any argument used in the constructor.

The HclustParam constructor will return a HclustParam object with the specified parameters.

The clusterRows method will return a factor of length equal to nrow(x) containing the cluster assignments. If full=TRUE, a list is returned with clusters (the factor, as above) and objects (the hclust output).

Aaron Lun

dist, hclust and cutree, which actually do all the heavy lifting.

cutreeDynamic, for an alternative tree cutting method to use in cut.fun.