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bioenv: bioenv

Citations

  • KR Clarke and M Ainsworth. A method of linking multivariate community structure to environmental variables. Marine ecology progress series, pages 205–219, 1993. doi:https://doi.org/10.3354/meps092205.

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.

Inputs:
  --i-distance-matrix ARTIFACT
    DistanceMatrix       Matrix of distances between pairs of samples.
                                                                    [required]
Parameters:
  --m-metadata-file METADATA...
    (multiple            The sample metadata.
     arguments will be
     merged)                                                        [required]
Outputs:
  --o-visualization VISUALIZATION
                                                                    [required]
Miscellaneous:
  --output-dir PATH      Output unspecified results to a directory
  --verbose / --quiet    Display verbose output to stdout and/or stderr
                         during execution of this action. Or silence output if
                         execution is successful (silence is golden).
  --example-data PATH    Write example data and exit.
  --citations            Show citations and exit.
  --use-cache DIRECTORY  Specify the cache to be used for the intermediate
                         work of this action. If not provided, the default
                         cache under $TMP/qiime2/ will be used.
                         IMPORTANT FOR HPC USERS: If you are on an HPC system
                         and are using parallel execution it is important to
                         set this to a location that is globally accessible to
                         all nodes in the cluster.
  --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