cluster_dimensions: Reorder samples and features by hierarchical clustering

In aaronwolen/metafiler: metagenomic profile plots

Reorder samples and features by hierarchical clustering

Description

Reorder samples or features of an ExpressionSet object based on agglomerative hierarchical clustering of their profiles.

Usage

cluster_samples(data, dist.method = "euclidean", hclust.method = "average")

## S3 method for class 'ExpressionSet'
cluster_samples(data, dist.method = "euclidean",
  hclust.method = "average")

cluster_features(data, dist.method = "euclidean", hclust.method = "average")

## S3 method for class 'ExpressionSet'
cluster_features(data, dist.method = "euclidean",
  hclust.method = "average")

Arguments

data	ExpressionSet object.
dist.method	distance metric to be calculated prior to clustering.
hclust.method	the agglomeration method to be used.

Details

Distance among samples or features is first calculated using the method specified by dist.method, which can be any of the measures accepted by dist. Similarly, hclust.method can be any of the agglomeration methods accepted by hclust.

Value

An ExpressionSet object reordered on one dimension.

See Also

dist, hclust

Examples

cluster_samples(profiles)
cluster_features(profiles)

aaronwolen/metafiler documentation built on Feb. 16, 2024, 12:41 a.m.