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volatility: Generate interactive volatility plot¶
Docstring:
Usage: qiime longitudinal volatility [OPTIONS]
Generate an interactive control chart depicting the longitudinal volatility
of sample metadata and/or feature frequencies across time (as set using the
"state_column" parameter). Any numeric metadata column (and metadata-
transformable artifacts, e.g., alpha diversity results) can be plotted on
the y-axis, and are selectable using the "metric_column" selector. Metric
values are averaged to compare across any categorical metadata column using
the "group_column" selector. Longitudinal volatility for individual subjects
sampled over time is co-plotted as "spaghetti" plots if the
"individual_id_column" parameter is used. state_column will typically be a
measure of time, but any numeric metadata column can be used.
Inputs:
--i-table ARTIFACT FeatureTable[RelativeFrequency]
Feature table containing metrics. [optional]
Parameters:
--m-metadata-file METADATA...
(multiple Sample metadata file containing
arguments will be individual-id-column.
merged) [required]
--p-state-column TEXT Metadata column containing state (time) variable
information. [required]
--p-individual-id-column TEXT
Metadata column containing IDs for individual
subjects. [optional]
--p-default-group-column TEXT
The default metadata column on which to separate
groups for comparison (all categorical metadata
columns will be available in the visualization).
[optional]
--p-default-metric TEXT
Numeric metadata or artifact column to test by
default (all numeric metadata columns will be
available in the visualization). [optional]
--p-yscale TEXT Choices('linear', 'pow', 'sqrt', 'log')
y-axis scaling strategy to apply. [default: 'linear']
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.
Examples:
# ### example: longitudinal volatility
qiime longitudinal volatility \
--m-metadata-file metadata.tsv \
--p-state-column month \
--o-visualization volatility-plot.qzv
Import:
from qiime2.plugins.longitudinal.visualizers import volatility
Docstring:
Generate interactive volatility plot
Generate an interactive control chart depicting the longitudinal volatility
of sample metadata and/or feature frequencies across time (as set using the
"state_column" parameter). Any numeric metadata column (and metadata-
transformable artifacts, e.g., alpha diversity results) can be plotted on
the y-axis, and are selectable using the "metric_column" selector. Metric
values are averaged to compare across any categorical metadata column using
the "group_column" selector. Longitudinal volatility for individual
subjects sampled over time is co-plotted as "spaghetti" plots if the
"individual_id_column" parameter is used. state_column will typically be a
measure of time, but any numeric metadata column can be used.
Parameters
----------
metadata : Metadata
Sample metadata file containing individual_id_column.
state_column : Str
Metadata column containing state (time) variable information.
individual_id_column : Str, optional
Metadata column containing IDs for individual subjects.
default_group_column : Str, optional
The default metadata column on which to separate groups for comparison
(all categorical metadata columns will be available in the
visualization).
default_metric : Str, optional
Numeric metadata or artifact column to test by default (all numeric
metadata columns will be available in the visualization).
table : FeatureTable[RelativeFrequency], optional
Feature table containing metrics.
yscale : Str % Choices('linear', 'pow', 'sqrt', 'log'), optional
y-axis scaling strategy to apply.
Returns
-------
visualization : Visualization