Docstring:
Usage: qiime longitudinal nmit [OPTIONS]
Perform nonparametric microbial interdependence test to determine
longitudinal sample similarity as a function of temporal microbial
composition. For more details and citation, please see
doi.org/10.1002/gepi.22065
Inputs:
--i-table ARTIFACT FeatureTable[RelativeFrequency]
Feature table to use for microbial interdependence
test. [required]
Parameters:
--m-metadata-file METADATA...
(multiple Sample metadata file containing individual-id-column.
arguments will be
merged) [required]
--p-individual-id-column TEXT
Metadata column containing IDs for individual
subjects. [required]
--p-corr-method TEXT Choices('kendall', 'pearson', 'spearman')
The temporal correlation test to be applied.
[default: 'kendall']
--p-dist-method TEXT Choices('fro', 'nuc')
Temporal distance method, see numpy.linalg.norm for
details. [default: 'fro']
Outputs:
--o-distance-matrix ARTIFACT
DistanceMatrix The resulting distance 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.longitudinal.methods import nmit
Docstring:
Nonparametric microbial interdependence test
Perform nonparametric microbial interdependence test to determine
longitudinal sample similarity as a function of temporal microbial
composition. For more details and citation, please see
doi.org/10.1002/gepi.22065
Parameters
----------
table : FeatureTable[RelativeFrequency]
Feature table to use for microbial interdependence test.
metadata : Metadata
Sample metadata file containing individual_id_column.
individual_id_column : Str
Metadata column containing IDs for individual subjects.
corr_method : Str % Choices('kendall', 'pearson', 'spearman'), optional
The temporal correlation test to be applied.
dist_method : Str % Choices('fro', 'nuc'), optional
Temporal distance method, see numpy.linalg.norm for details.
Returns
-------
distance_matrix : DistanceMatrix
The resulting distance matrix.
