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adonis: adonis PERMANOVA test for beta group significance

Citations
  • Marti J Anderson. A new method for non-parametric multivariate analysis of variance. Austral ecology, 26(1):32–46, 2001. doi:https://doi.org/10.1111/j.1442-9993.2001.01070.pp.x.

  • Jari Oksanen, F. Guillaume Blanchet, Michael Friendly, Roeland Kindt, Pierre Legendre, Dan McGlinn, Peter R. Minchin, R. B. O’Hara, Gavin L. Simpson, Peter Solymos, M. Henry H. Stevens, Eduard Szoecs, and Helene Wagner. vegan: Community Ecology Package. 2018. R package version 2.5-3. URL: https://CRAN.R-project.org/package=vegan.

Docstring:

Usage: qiime diversity adonis [OPTIONS]

  Determine whether groups of samples are significantly different from one
  another using the ADONIS permutation-based statistical test in vegan-R.
  The function partitions sums of squares of a multivariate data set, and is
  directly analogous to MANOVA (multivariate analysis of variance). This
  action differs from beta_group_significance in that it accepts R formulae
  to perform multi-way ADONIS tests; beta_group_signficance only performs
  one-way tests. For more details see
  http://cc.oulu.fi/~jarioksa/softhelp/vegan/html/adonis.html

Inputs:
  --i-distance-matrix ARTIFACT
    DistanceMatrix     Matrix of distances between pairs of samples.
                                                                    [required]
Parameters:
  --m-metadata-file METADATA...
    (multiple          Sample metadata containing formula terms.
     arguments will
     be merged)                                                     [required]
  --p-formula TEXT     Model formula containing only independent terms
                       contained in the sample metadata. These can be
                       continuous variables or factors, and they can have
                       interactions as in a typical R formula. E.g., the
                       formula "treatment+block" would test whether the input
                       distance matrix partitions based on "treatment" and
                       "block" sample metadata. The formula "treatment*block"
                       would test both of those effects as well as their
                       interaction. Enclose formulae in quotes to avoid
                       unpleasant surprises.                        [required]
  --p-permutations INTEGER
    Range(1, None)     The number of permutations to be run when computing
                       p-values.                                [default: 999]
  --p-n-jobs INTEGER   Number of parallel processes to run.
    Range(1, None)                                                [default: 1]
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 adonis

Docstring:

adonis PERMANOVA test for beta group significance

Determine whether groups of samples are significantly different from one
another using the ADONIS permutation-based statistical test in vegan-R. The
function partitions sums of squares of a multivariate data set, and is
directly analogous to MANOVA (multivariate analysis of variance). This
action differs from beta_group_significance in that it accepts R formulae
to perform multi-way ADONIS tests; beta_group_signficance only performs
one-way tests. For more details see
http://cc.oulu.fi/~jarioksa/softhelp/vegan/html/adonis.html

Parameters
----------
distance_matrix : DistanceMatrix
    Matrix of distances between pairs of samples.
metadata : Metadata
    Sample metadata containing formula terms.
formula : Str
    Model formula containing only independent terms contained in the sample
    metadata. These can be continuous variables or factors, and they can
    have interactions as in a typical R formula. E.g., the formula
    "treatment+block" would test whether the input distance matrix
    partitions based on "treatment" and "block" sample metadata. The
    formula "treatment*block" would test both of those effects as well as
    their interaction. Enclose formulae in quotes to avoid unpleasant
    surprises.
permutations : Int % Range(1, None), optional
    The number of permutations to be run when computing p-values.
n_jobs : Int % Range(1, None), optional
    Number of parallel processes to run.

Returns
-------
visualization : Visualization