Docstring:
Usage: qiime longitudinal pairwise-distances [OPTIONS]
Performs pairwise distance testing between sample pairs from each subject.
Sample pairs may represent a typical intervention study, e.g., samples
collected pre- and post-treatment; paired samples from two different
timepoints (e.g., in a longitudinal study design), or identical samples
receiving different two different treatments. This action tests whether the
pairwise distance between each subject pair differs between groups (e.g.,
groups of subjects receiving different treatments) and produces boxplots of
paired distance distributions for each group.
Inputs:
--i-distance-matrix ARTIFACT
DistanceMatrix Matrix of distances between pairs of samples.
[required]
Parameters:
--m-metadata-file METADATA...
(multiple Sample metadata file containing
arguments will be individual-id-column.
merged) [required]
--p-group-column TEXT Metadata column on which to separate groups for
comparison [required]
--p-state-column TEXT Metadata column containing state (e.g., Time) across
which samples are paired. [required]
--p-state-1 TEXT Baseline state column value. [required]
--p-state-2 TEXT State column value to pair with baseline. [required]
--p-individual-id-column TEXT
Metadata column containing subject IDs to use for
pairing samples. WARNING: if replicates exist for an
individual ID at either state-1 or state-2, that
subject will be dropped and reported in standard
output by default. Set replicate_handling="random" to
instead randomly select one member. [required]
--p-parametric / --p-no-parametric
Perform parametric (ANOVA and t-tests) or
non-parametric (Kruskal-Wallis, Wilcoxon, and
Mann-Whitney U tests) statistical tests.
[default: False]
--p-palette TEXT Choices('Set1', 'Set2', 'Set3', 'Pastel1', 'Pastel2',
'Paired', 'Accent', 'Dark2', 'tab10', 'tab20', 'tab20b', 'tab20c',
'viridis', 'plasma', 'inferno', 'magma', 'terrain', 'rainbow', 'cividis')
Color palette to use for generating boxplots.
[default: 'Set1']
--p-replicate-handling TEXT Choices('error', 'random', 'drop')
Choose how replicate samples are handled. If
replicates are detected, "error" causes method to
fail; "drop" will discard all replicated samples;
"random" chooses one representative at random from
among replicates. [default: 'error']
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.
--help Show this message and exit.
Import:
from qiime2.plugins.longitudinal.visualizers import pairwise_distances
Docstring:
Paired pairwise distance testing and boxplots
Performs pairwise distance testing between sample pairs from each subject.
Sample pairs may represent a typical intervention study, e.g., samples
collected pre- and post-treatment; paired samples from two different
timepoints (e.g., in a longitudinal study design), or identical samples
receiving different two different treatments. This action tests whether the
pairwise distance between each subject pair differs between groups (e.g.,
groups of subjects receiving different treatments) and produces boxplots of
paired distance distributions for each group.
Parameters
----------
distance_matrix : DistanceMatrix
Matrix of distances between pairs of samples.
metadata : Metadata
Sample metadata file containing individual_id_column.
group_column : Str
Metadata column on which to separate groups for comparison
state_column : Str
Metadata column containing state (e.g., Time) across which samples are
paired.
state_1 : Str
Baseline state column value.
state_2 : Str
State column value to pair with baseline.
individual_id_column : Str
Metadata column containing subject IDs to use for pairing samples.
WARNING: if replicates exist for an individual ID at either state_1 or
state_2, that subject will be dropped and reported in standard output
by default. Set replicate_handling="random" to instead randomly select
one member.
parametric : Bool, optional
Perform parametric (ANOVA and t-tests) or non-parametric (Kruskal-
Wallis, Wilcoxon, and Mann-Whitney U tests) statistical tests.
palette : Str % Choices('Set1', 'Set2', 'Set3', 'Pastel1', 'Pastel2', 'Paired', 'Accent', 'Dark2', 'tab10', 'tab20', 'tab20b', 'tab20c', 'viridis', 'plasma', 'inferno', 'magma', 'terrain', 'rainbow', 'cividis'), optional
Color palette to use for generating boxplots.
replicate_handling : Str % Choices('error', 'random', 'drop'), optional
Choose how replicate samples are handled. If replicates are detected,
"error" causes method to fail; "drop" will discard all replicated
samples; "random" chooses one representative at random from among
replicates.
Returns
-------
visualization : Visualization
