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).
--example-data PATH Write example data and exit.
--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.