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bioenv: bioenv

Citations

[diversity:bioenv:CA93]KR Clarke and M Ainsworth. A method of linking multivariate community structure to environmental variables. Marine ecology progress series, pages 205–219, 1993.

Docstring:

Usage: qiime diversity bioenv [OPTIONS]

  Find the subsets of variables in metadata whose Euclidean distances are
  maximally rank-correlated with distance matrix. All numeric variables in
  metadata will be considered, and samples which are missing data will be
  dropped. The output visualization will indicate how many samples were
  dropped due to missing data, if any were dropped.

Options:
  --i-distance-matrix ARTIFACT PATH DistanceMatrix
                                  Matrix of distances between pairs of
                                  samples.  [required]
  --m-metadata-file MULTIPLE FILE
                                  Metadata file or artifact viewable as
                                  metadata. This option may be supplied
                                  multiple times to merge metadata. The sample
                                  metadata.  [required]
  --o-visualization VISUALIZATION PATH
                                  [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.diversity.visualizers import bioenv

Docstring:

bioenv

Find the subsets of variables in metadata whose Euclidean distances are
maximally rank-correlated with distance matrix. All numeric variables in
metadata will be considered, and samples which are missing data will be
dropped. The output visualization will indicate how many samples were
dropped due to missing data, if any were dropped.

Parameters
----------
distance_matrix : DistanceMatrix
    Matrix of distances between pairs of samples.
metadata : Metadata
    The sample metadata.

Returns
-------
visualization : Visualization