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pcoa-biplot: Principal Coordinate Analysis BiplotΒΆ

Citations
  • Pierre Legendre and Louis Legendre. Numerical Ecology, pages 499. Elsevier, Third edition, 2012.

Docstring:

Usage: qiime diversity pcoa-biplot [OPTIONS]

  Project features into a principal coordinates matrix. The features used
  should be the features used to compute the distance matrix. It is
  recommended that these variables be normalized in cases of dimensionally
  heterogeneous physical variables.

Inputs:
  --i-pcoa ARTIFACT      The PCoA where the features will be projected onto.
    PCoAResults                                                     [required]
  --i-features ARTIFACT FeatureTable[RelativeFrequency]
                         Variables to project onto the PCoA matrix  [required]
Outputs:
  --o-biplot ARTIFACT PCoAResults % Properties('biplot')
                         The resulting PCoA matrix.                 [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.methods import pcoa_biplot

Docstring:

Principal Coordinate Analysis Biplot

Project features into a principal coordinates matrix. The features used
should be the features used to compute the distance matrix. It is
recommended that these variables be normalized in cases of dimensionally
heterogeneous physical variables.

Parameters
----------
pcoa : PCoAResults
    The PCoA where the features will be projected onto.
features : FeatureTable[RelativeFrequency]
    Variables to project onto the PCoA matrix

Returns
-------
biplot : PCoAResults % Properties('biplot')
    The resulting PCoA matrix.