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pcoa-biplot: Principal Coordinate Analysis Biplot¶
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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. --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.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.