Reorder or Group observations based on hierarchical clustering

This function aligns observations within the layout according to a hierarchical clustering tree, enabling reordering or grouping of elements based on clustering results.

Usage

align_hclust(
  distance = "euclidean",
  method = "complete",
  use_missing = "pairwise.complete.obs",
  reorder_dendrogram = FALSE,
  reorder_group = FALSE,
  k = NULL,
  h = NULL,
  cutree = NULL,
  data = NULL,
  active = NULL
)

Arguments

distance

A string of distance measure to be used. This must be one of "euclidean", "maximum", "manhattan", "canberra", "binary" or "minkowski". Correlation coefficient can be also used, including "pearson", "spearman" or "kendall". In this way, 1 - cor will be used as the distance. In addition, you can also provide a dist object directly or a function return a dist object. Use NULL, if you don't want to calculate the distance.

method

A string of the agglomeration method to be used. This should be (an unambiguous abbreviation of) one of "ward.D", "ward.D2", "single", "complete", "average" (= UPGMA), "mcquitty" (= WPGMA), "median" (= WPGMC) or "centroid" (= UPGMC). You can also provide a function which accepts the calculated distance (or the input matrix if distance is NULL) and returns a hclust object. Alternative, you can supply an object which can be coerced to hclust.

use_missing

An optional character string giving a method for computing covariances in the presence of missing values. This must be (an abbreviation of) one of the strings "everything", "all.obs", "complete.obs", "na.or.complete", or "pairwise.complete.obs". Only used when distance is a correlation coefficient string.

reorder_dendrogram

A single boolean value indicating whether to reorder the dendrogram based on the means. Alternatively, you can provide a custom function that accepts an hclust object and the data used to generate the tree, returning either an hclust or dendrogram object. Default is FALSE.

reorder_group

A single boolean value, indicates whether we should do Hierarchical Clustering between groups, only used when previous groups have been established. Default: FALSE.

k

An integer scalar indicates the desired number of groups.

h

A numeric scalar indicates heights where the tree should be cut.

cutree

A function used to cut the hclust tree. It should accept four arguments: the hclust tree object, distance (only applicable when method is a string or a function for performing hierarchical clustering), k (the number of clusters), and h (the height at which to cut the tree). By default, cutree() is used.

data

A matrix-like object. By default, it inherits from the layout matrix.

active

A active() object that defines the context settings when added to a layout.

Discrete Axis Alignment

It is important to note that we consider rows as observations, meaning vec_size(data)/NROW(data) must match the number of observations along the axis used for alignment (x-axis for a vertical stack layout, y-axis for a horizontal stack layout).

See also

hclust2()

Examples

# align_hclust won't add a dendrogram
ggheatmap(matrix(rnorm(81), nrow = 9)) +
    anno_top() +
    align_hclust(k = 3L)
#> → heatmap built with `geom_tile()`