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weighted-unifrac: Weighted Unifrac¶
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Docstring:
Usage: qiime diversity-lib weighted-unifrac [OPTIONS]
Compute Weighted Unifrac for each sample in a feature table
Inputs:
--i-table ARTIFACT FeatureTable[Frequency | RelativeFrequency]
The feature table containing the samples for which
Weighted Unifrac 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-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-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 Distance matrix for Unweighted Unifrac. [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: run on one core (by default)
qiime diversity-lib weighted-unifrac \
--i-table feature-table.qza \
--i-phylogeny phylogeny.qza \
--o-distance-matrix weighted-unifrac-dm.qza
# ### example: to run on n cores, replace 1 here with your preferred integer
qiime diversity-lib weighted-unifrac \
--i-table feature-table.qza \
--i-phylogeny phylogeny.qza \
--p-threads 1 \
--o-distance-matrix weighted-unifrac-dm.qza
# ### example: use 'auto' to run on all of host system's available CPU cores
qiime diversity-lib weighted-unifrac \
--i-table feature-table.qza \
--i-phylogeny phylogeny.qza \
--p-threads auto \
--o-distance-matrix weighted-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 weighted-unifrac \
--i-table feature-table.qza \
--i-phylogeny phylogeny.qza \
--p-threads auto \
--p-bypass-tips \
--o-distance-matrix weighted-unifrac-dm.qza
Import:
from qiime2.plugins.diversity_lib.methods import weighted_unifrac
Docstring:
Weighted Unifrac
Compute Weighted Unifrac for each sample in a feature table
Parameters
----------
table : FeatureTable[Frequency | RelativeFrequency]
The feature table containing the samples for which Weighted Unifrac
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.
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.
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
Distance matrix for Unweighted Unifrac.