Identify Independent Features in a Numeric Matrix

This function identifies independent features using Spearman's rho correlation distances, and a dendrogram tree cut step.

Usage

tree_and_independent_features(
  data,
  tree_cut_height = 0.5,
  features_exclude = NULL
)

Arguments

data

matrix, the metabolite data matrix. samples in row, metabolites in columns

tree_cut_height

the tree cut height. A value of 0.2 (1-Spearman's rho) is equivalent to saying that features with a rho >= 0.8 are NOT independent.

features_exclude

character, vector of feature id indicating features to exclude from the sample and PCA summary analysis but keep in the data

Value

a list object of (1) an hclust object, (2) independent features, (3) a data frame of feature ids, k-cluster identifiers, and a binary identifier of independent features