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beta-phylogenetic-passthrough: Beta Phylogenetic Passthrough

Citations

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.