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gradient-clustering: Hierarchical clustering using gradient information.ΒΆ

Docstring:

Usage: qiime gneiss gradient-clustering [OPTIONS]

  Build a bifurcating tree that represents a hierarchical clustering of
  features.  The hiearchical clustering uses Ward hierarchical clustering
  based on the mean difference of gradients that each feature is observed
  in. This method is primarily used to sort the table to reveal the
  underlying block-like structures.

Options:
  --i-table ARTIFACT PATH FeatureTable[Composition | Frequency | RelativeFrequency]
                                  The feature table containing the samples in
                                  which the columns will be clustered.
                                  [required]
  --m-gradient-file MULTIPLE FILE
                                  Metadata file or artifact viewable as
                                  metadata. This option may be supplied
                                  multiple times to merge metadata.
                                  [required]
  --m-gradient-column MetadataColumn[Numeric]
                                  Column from metadata file or artifact
                                  viewable as metadata. Contains gradient
                                  values to sort the features and samples.
                                  [required]
  --p-weighted / --p-no-weighted  Specifies if abundance or presence/absence
                                  information should be used to perform the
                                  clustering.  [default: True]
  --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 gradient_clustering

Docstring:

Hierarchical clustering using gradient information.

Build a bifurcating tree that represents a hierarchical clustering of
features.  The hiearchical clustering uses Ward hierarchical clustering
based on the mean difference of gradients that each feature is observed in.
This method is primarily used to sort the table to reveal the underlying
block-like structures.

Parameters
----------
table : FeatureTable[Composition | Frequency | RelativeFrequency]
    The feature table containing the samples in which the columns will be
    clustered.
gradient : MetadataColumn[Numeric]
    Contains gradient values to sort the features and samples.
weighted : Bool, optional
    Specifies if abundance or presence/absence information should be used
    to perform the clustering.

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.