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beta-group-significance: Beta diversity group significance

Citations

Docstring:

Usage: qiime diversity beta-group-significance [OPTIONS]

  Determine whether groups of samples are significantly different from one
  another using a permutation-based statistical test.

Inputs:
  --i-distance-matrix ARTIFACT
    DistanceMatrix     Matrix of distances between pairs of samples.
                                                                    [required]
Parameters:
  --m-metadata-file METADATA
  --m-metadata-column COLUMN  MetadataColumn[Categorical]
                       Categorical sample metadata column.          [required]
  --p-method TEXT Choices('permanova', 'anosim', 'permdisp')
                       The group significance test to be applied.
                                                        [default: 'permanova']
  --p-pairwise / --p-no-pairwise
                       Perform pairwise tests between all pairs of groups in
                       addition to the test across all groups. This can be
                       very slow if there are a lot of groups in the metadata
                       column.                                [default: False]
  --p-permutations INTEGER
                       The number of permutations to be run when computing
                       p-values.                                [default: 999]
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).
  --citations          Show citations and exit.
  --help               Show this message and exit.

Import:

from qiime2.plugins.diversity.visualizers import beta_group_significance

Docstring:

Beta diversity group significance

Determine whether groups of samples are significantly different from one
another using a permutation-based statistical test.

Parameters
----------
distance_matrix : DistanceMatrix
    Matrix of distances between pairs of samples.
metadata : MetadataColumn[Categorical]
    Categorical sample metadata column.
method : Str % Choices('permanova', 'anosim', 'permdisp'), optional
    The group significance test to be applied.
pairwise : Bool, optional
    Perform pairwise tests between all pairs of groups in addition to the
    test across all groups. This can be very slow if there are a lot of
    groups in the metadata column.
permutations : Int, optional
    The number of permutations to be run when computing p-values.

Returns
-------
visualization : Visualization