Docstring:
Usage: qiime diversity-lib beta-phylogenetic-passthrough [OPTIONS]
Computes a distance matrix for all pairs of samples in a feature table using
the unifrac implementation of the selected beta diversity metric.
Inputs:
--i-table ARTIFACT FeatureTable[Frequency]
The feature table containing the samples over which
beta diversity should be computed. [required]
--i-phylogeny ARTIFACT Phylogenetic tree containing tip identifiers that
Phylogeny[Rooted] correspond to the feature identifiers in the table.
This tree can contain tip ids that are not present
in the table, but all feature ids in the table must
be present in this tree. [required]
Parameters:
--p-metric TEXT Choices('generalized_unifrac', 'unweighted_unifrac',
'weighted_normalized_unifrac', 'weighted_unifrac')
The beta diversity metric to be computed. [required]
--p-threads NTHREADS The number of CPU threads to use in performing this
calculation. May not exceed the number of available
physical cores. If threads = 'auto', one thread will
be created for each identified CPU core on the host.
[default: 1]
--p-variance-adjusted / --p-no-variance-adjusted
Perform variance adjustment based on Chang et al.
BMC Bioinformatics 2011. Weights distances based on
the proportion of the relative abundance represented
between the samples at a given node under
evaluation. [default: False]
--p-alpha PROPORTION Range(0, 1, inclusive_end=True)
This parameter is only used when the choice of
metric is generalized_unifrac. The value of alpha
controls importance of sample proportions. 1.0 is
weighted normalized UniFrac. 0.0 is close to
unweighted UniFrac, but only if the sample
proportions are dichotomized. [optional]
--p-bypass-tips / --p-no-bypass-tips
In a bifurcating tree, the tips make up about 50%
of the nodes in a tree. By ignoring them,
specificity can be traded for reduced compute time.
This has the effect of collapsing the phylogeny, and
is analogous (in concept) to moving from 99% to 97%
OTUs [default: False]
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.
Examples:
# ### example: run on one core (by default)
qiime diversity-lib beta-phylogenetic-passthrough \
--i-table feature-table.qza \
--i-phylogeny phylogeny.qza \
--p-metric weighted_normalized_unifrac \
--o-distance-matrix weighted-normalized-unifrac-dm.qza
# ### example: to run on n cores, replace 1 here with your preferred integer
qiime diversity-lib beta-phylogenetic-passthrough \
--i-table feature-table.qza \
--i-phylogeny phylogeny.qza \
--p-threads 1 \
--p-metric weighted_normalized_unifrac \
--o-distance-matrix weighted-normalized-unifrac-dm.qza
# ### example: use 'auto' to run on all of host system's available CPU cores
qiime diversity-lib beta-phylogenetic-passthrough \
--i-table feature-table.qza \
--i-phylogeny phylogeny.qza \
--p-threads auto \
--p-metric weighted_normalized_unifrac \
--o-distance-matrix weighted-normalized-unifrac-dm.qza
# ### example: use bypass tips to trade specificity for reduced compute time
# bypass_tips can be used with any threads setting, but auto may be a good
# choice if you're trimming run time.
qiime diversity-lib beta-phylogenetic-passthrough \
--i-table feature-table.qza \
--i-phylogeny phylogeny.qza \
--p-metric weighted_normalized_unifrac \
--p-threads auto \
--p-bypass-tips \
--o-distance-matrix weighted-normalized-unifrac-dm.qza
# ### example: variance adjustment
# Chang et al's variance adjustment may be applied to any unifrac method by
# using this passthrough function.
qiime diversity-lib beta-phylogenetic-passthrough \
--i-table feature-table.qza \
--i-phylogeny phylogeny.qza \
--p-metric weighted_unifrac \
--p-threads auto \
--p-variance-adjusted \
--o-distance-matrix var-adj-weighted-unifrac-dm.qza
# ### example: minimal generalized unifrac
# Generalized unifrac is passed alpha=1 by default. This is roughly
# equivalent to weighted normalized unifrac, which method will be used
# instead, because it is better optimized.
qiime diversity-lib beta-phylogenetic-passthrough \
--i-table feature-table.qza \
--i-phylogeny phylogeny.qza \
--p-metric generalized_unifrac \
--o-distance-matrix generalized-unifrac-dm.qza
# ### example: generalized unifrac
# passing a float between 0 and 1 to 'alpha' gives you control over the
# importance of sample proportions.
qiime diversity-lib beta-phylogenetic-passthrough \
--i-table feature-table.qza \
--i-phylogeny phylogeny.qza \
--p-metric generalized_unifrac \
--p-alpha 0.75 \
--o-distance-matrix generalized-unifrac-dm.qza
Import:
from qiime2.plugins.diversity_lib.methods import beta_phylogenetic_passthrough
Docstring:
Beta Phylogenetic Passthrough
Computes a distance matrix for all pairs of samples in a feature table
using the unifrac implementation of the selected beta diversity metric.
Parameters
----------
table : FeatureTable[Frequency]
The feature table containing the samples over which beta diversity
should be computed.
phylogeny : Phylogeny[Rooted]
Phylogenetic tree containing tip identifiers that correspond to the
feature identifiers in the table. This tree can contain tip ids that
are not present in the table, but all feature ids in the table must be
present in this tree.
metric : Str % Choices('generalized_unifrac', 'unweighted_unifrac', 'weighted_normalized_unifrac', 'weighted_unifrac')
The beta diversity metric to be computed.
threads : Threads, optional
The number of CPU threads to use in performing this calculation. May
not exceed the number of available physical cores. If threads = 'auto',
one thread will be created for each identified CPU core on the host.
variance_adjusted : Bool, optional
Perform variance adjustment based on Chang et al. BMC Bioinformatics
2011. Weights distances based on the proportion of the relative
abundance represented between the samples at a given node under
evaluation.
alpha : Float % Range(0, 1, inclusive_end=True), optional
This parameter is only used when the choice of metric is
generalized_unifrac. The value of alpha controls importance of sample
proportions. 1.0 is weighted normalized UniFrac. 0.0 is close to
unweighted UniFrac, but only if the sample proportions are
dichotomized.
bypass_tips : Bool, optional
In a bifurcating tree, the tips make up about 50% of the nodes in a
tree. By ignoring them, specificity can be traded for reduced compute
time. This has the effect of collapsing the phylogeny, and is analogous
(in concept) to moving from 99% to 97% OTUs
Returns
-------
distance_matrix : DistanceMatrix
The resulting distance matrix.
