Docstring:
Usage: qiime diversity-lib beta-phylogenetic-meta-passthrough
[OPTIONS]
Computes a distance matrix for all pairs of samples in the set of feature
table and phylogeny pairs, using the unifrac implementation of the selected
beta diversity metric.
Inputs:
--i-tables ARTIFACTS... List[FeatureTable[Frequency]]
The feature tables containing the samples over
which beta diversity should be computed. [required]
--i-phylogenies ARTIFACTS... List[Phylogeny[Rooted]]
Phylogenetic trees 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. [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]
--p-weights NUMBERS... The weight applied to each tree/table pair. This
List[Float] tuple is expected to be in index order with tables
and phylogenies. Default is to weight each
tree/table pair evenly. [optional]
--p-consolidation TEXT Choices('skipping_missing_matrices',
'missing_zero', 'missing_one', 'skipping_missing_values')
The matrix consolidation method, which determines
how the individual distance matrices are aggregated
[default: 'skipping_missing_values']
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.
--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: Basic meta unifrac
# For brevity, these examples are focused on meta-specific parameters. See
# the documentation for beta_phylogenetic_passthrough for additional
# relevant information.
# NOTE: the number of trees and tables must match.
qiime diversity-lib beta-phylogenetic-meta-passthrough \
--i-tables feature-table1.qza feature-table2.qza \
--i-phylogenies phylogeny1.qza phylogeny2.qza \
--p-metric weighted_normalized_unifrac \
--o-distance-matrix ft1-ft2-w-norm-unifrac-dm.qza
# ### example: meta with weights
# The number of weights must match the number of tables/trees.
# If meaningful, it is possible to pass the same phylogeny more than once.
qiime diversity-lib beta-phylogenetic-meta-passthrough \
--i-tables feature-table1.qza feature-table2.qza \
--i-phylogenies phylogeny.qza phylogeny.qza \
--p-metric weighted_normalized_unifrac \
--p-weights 3.0 42.0 \
--o-distance-matrix ft1-ft2-w-norm-unifrac-dm.qza
# ### example: changing the consolidation method
qiime diversity-lib beta-phylogenetic-meta-passthrough \
--i-tables feature-table1.qza feature-table2.qza \
--i-phylogenies phylogeny1.qza phylogeny2.qza \
--p-metric weighted_normalized_unifrac \
--p-weights 0.4 0.6 \
--p-consolidation skipping_missing_values \
--o-distance-matrix ft1-ft2-w-norm-unifrac-dm.qza
Import:
from qiime2.plugins.diversity_lib.methods import beta_phylogenetic_meta_passthrough
Docstring:
Beta Phylogenetic Meta Passthrough
Computes a distance matrix for all pairs of samples in the set of feature
table and phylogeny pairs, using the unifrac implementation of the selected
beta diversity metric.
Parameters
----------
tables : List[FeatureTable[Frequency]]
The feature tables containing the samples over which beta diversity
should be computed.
phylogenies : List[Phylogeny[Rooted]]
Phylogenetic trees 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
weights : List[Float], optional
The weight applied to each tree/table pair. This tuple is expected to
be in index order with tables and phylogenies. Default is to weight
each tree/table pair evenly.
consolidation : Str % Choices('skipping_missing_matrices', 'missing_zero', 'missing_one', 'skipping_missing_values'), optional
The matrix consolidation method, which determines how the individual
distance matrices are aggregated
Returns
-------
distance_matrix : DistanceMatrix
The resulting distance matrix.
