Docstring:
Usage: qiime diversity bioenv [OPTIONS]
Find the subsets of variables in metadata whose Euclidean distances are
maximally rank-correlated with distance matrix. All numeric variables in
metadata will be considered, and samples which are missing data will be
dropped. The output visualization will indicate how many samples were
dropped due to missing data, if any were dropped.
Inputs:
--i-distance-matrix ARTIFACT
DistanceMatrix Matrix of distances between pairs of samples.
[required]
Parameters:
--m-metadata-file METADATA...
(multiple The sample metadata.
arguments will be
merged) [required]
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).
--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.visualizers import bioenv
Docstring:
bioenv
Find the subsets of variables in metadata whose Euclidean distances are
maximally rank-correlated with distance matrix. All numeric variables in
metadata will be considered, and samples which are missing data will be
dropped. The output visualization will indicate how many samples were
dropped due to missing data, if any were dropped.
Parameters
----------
distance_matrix : DistanceMatrix
Matrix of distances between pairs of samples.
metadata : Metadata
The sample metadata.
Returns
-------
visualization : Visualization