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correlation-clustering: Hierarchical clustering using feature correlation.ΒΆ

Docstring:

Usage: qiime gneiss correlation-clustering [OPTIONS]

  Build a bifurcating tree that represents a hierarchical clustering of
  features.  The hiearchical clustering uses Ward hierarchical clustering
  based on the degree of proportionality between features.

Options:
  --i-table ARTIFACT PATH FeatureTable[Frequency]
                                  The feature table containing the samples in
                                  which the columns will be clustered.
                                  [required]
  --p-pseudocount FLOAT           The value to add to zero counts in the
                                  feature table.  [default: 0.5]
  --o-clustering ARTIFACT PATH Hierarchy
                                  A hierarchy of feature identifiers where
                                  each tip corresponds to the feature
                                  identifiers in the table. This tree can
                                  contain tip ids that are not present in the
                                  table, but all feature ids in the table must
                                  be present in this tree.  [required if not
                                  passing --output-dir]
  --output-dir DIRECTORY          Output unspecified results to a directory
  --cmd-config FILE               Use config file for command options
  --verbose                       Display verbose output to stdout and/or
                                  stderr during execution of this action.
                                  [default: False]
  --quiet                         Silence output if execution is successful
                                  (silence is golden).  [default: False]
  --citations                     Show citations and exit.
  --help                          Show this message and exit.

Import:

from qiime2.plugins.gneiss.methods import correlation_clustering

Docstring:

Hierarchical clustering using feature correlation.

Build a bifurcating tree that represents a hierarchical clustering of
features.  The hiearchical clustering uses Ward hierarchical clustering
based on the degree of proportionality between features.

Parameters
----------
table : FeatureTable[Frequency]
    The feature table containing the samples in which the columns will be
    clustered.
pseudocount : Float, optional
    The value to add to zero counts in the feature table.

Returns
-------
clustering : Hierarchy
    A hierarchy of feature identifiers where each tip corresponds to the
    feature identifiers in the table. This tree can contain tip ids that
    are not present in the table, but all feature ids in the table must be
    present in this tree.