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core-metrics: Core diversity metrics (non-phylogenetic)ΒΆ

Docstring:

Usage: qiime diversity core-metrics [OPTIONS]

  Applies a collection of diversity metrics (non-phylogenetic) to a feature
  table.

Options:
  --i-table ARTIFACT PATH FeatureTable[Frequency]
                                  The feature table containing the samples
                                  over which diversity metrics should be
                                  computed.  [required]
  --p-sampling-depth INTEGER RANGE
                                  The total frequency that each sample should
                                  be rarefied to prior to computing diversity
                                  metrics.  [required]
  --m-metadata-file MULTIPLE FILE
                                  Metadata file or artifact viewable as
                                  metadata. This option may be supplied
                                  multiple times to merge metadata. The sample
                                  metadata to use in the emperor plots.
                                  [required]
  --p-n-jobs INTEGER RANGE        [beta methods only] - The number of jobs to
                                  use for the computation. This works by
                                  breaking down the pairwise matrix into
                                  n_jobs even slices and computing them in
                                  parallel. If -1 all CPUs are used. If 1 is
                                  given, no parallel computing code is used at
                                  all, which is useful for debugging. For
                                  n_jobs below -1, (n_cpus + 1 + n_jobs) are
                                  used. Thus for n_jobs = -2, all CPUs but one
                                  are used. (Description from
                                  sklearn.metrics.pairwise_distances)
                                  [default: 1]
  --o-rarefied-table ARTIFACT PATH FeatureTable[Frequency]
                                  The resulting rarefied feature table.
                                  [required if not passing --output-dir]
  --o-observed-otus-vector ARTIFACT PATH SampleData[AlphaDiversity]
                                  Vector of Observed OTUs values by sample.
                                  [required if not passing --output-dir]
  --o-shannon-vector ARTIFACT PATH SampleData[AlphaDiversity]
                                  Vector of Shannon diversity values by
                                  sample.  [required if not passing --output-
                                  dir]
  --o-evenness-vector ARTIFACT PATH SampleData[AlphaDiversity]
                                  Vector of Pielou's evenness values by
                                  sample.  [required if not passing --output-
                                  dir]
  --o-jaccard-distance-matrix ARTIFACT PATH DistanceMatrix
                                  Matrix of Jaccard distances between pairs of
                                  samples.  [required if not passing --output-
                                  dir]
  --o-bray-curtis-distance-matrix ARTIFACT PATH DistanceMatrix
                                  Matrix of Bray-Curtis distances between
                                  pairs of samples.  [required if not passing
                                  --output-dir]
  --o-jaccard-pcoa-results ARTIFACT PATH PCoAResults
                                  PCoA matrix computed from Jaccard distances
                                  between samples.  [required if not passing
                                  --output-dir]
  --o-bray-curtis-pcoa-results ARTIFACT PATH PCoAResults
                                  PCoA matrix computed from Bray-Curtis
                                  distances between samples.  [required if not
                                  passing --output-dir]
  --o-jaccard-emperor VISUALIZATION PATH
                                  Emperor plot of the PCoA matrix computed
                                  from Jaccard.  [required if not passing
                                  --output-dir]
  --o-bray-curtis-emperor VISUALIZATION PATH
                                  Emperor plot of the PCoA matrix computed
                                  from Bray-Curtis.  [required if not passing
                                  --output-dir]
  --output-dir DIRECTORY          Output unspecified results to a directory
  --cmd-config FILE               Use config file for command options
  --verbose                       Display verbose output to stdout and/or
                                  stderr during execution of this action.
                                  [default: False]
  --quiet                         Silence output if execution is successful
                                  (silence is golden).  [default: False]
  --citations                     Show citations and exit.
  --help                          Show this message and exit.

Import:

from qiime2.plugins.diversity.pipelines import core_metrics

Docstring:

Core diversity metrics (non-phylogenetic)

Applies a collection of diversity metrics (non-phylogenetic) to a feature
table.

Parameters
----------
table : FeatureTable[Frequency]
    The feature table containing the samples over which diversity metrics
    should be computed.
sampling_depth : Int % Range(1, None)
    The total frequency that each sample should be rarefied to prior to
    computing diversity metrics.
metadata : Metadata
    The sample metadata to use in the emperor plots.
n_jobs : Int % Range(0, None), optional
    [beta methods only] - The number of jobs to use for the computation.
    This works by breaking down the pairwise matrix into n_jobs even slices
    and computing them in parallel. If -1 all CPUs are used. If 1 is given,
    no parallel computing code is used at all, which is useful for
    debugging. For n_jobs below -1, (n_cpus + 1 + n_jobs) are used. Thus
    for n_jobs = -2, all CPUs but one are used. (Description from
    sklearn.metrics.pairwise_distances)

Returns
-------
rarefied_table : FeatureTable[Frequency]
    The resulting rarefied feature table.
observed_otus_vector : SampleData[AlphaDiversity]
    Vector of Observed OTUs values by sample.
shannon_vector : SampleData[AlphaDiversity]
    Vector of Shannon diversity values by sample.
evenness_vector : SampleData[AlphaDiversity]
    Vector of Pielou's evenness values by sample.
jaccard_distance_matrix : DistanceMatrix
    Matrix of Jaccard distances between pairs of samples.
bray_curtis_distance_matrix : DistanceMatrix
    Matrix of Bray-Curtis distances between pairs of samples.
jaccard_pcoa_results : PCoAResults
    PCoA matrix computed from Jaccard distances between samples.
bray_curtis_pcoa_results : PCoAResults
    PCoA matrix computed from Bray-Curtis distances between samples.
jaccard_emperor : Visualization
    Emperor plot of the PCoA matrix computed from Jaccard.
bray_curtis_emperor : Visualization
    Emperor plot of the PCoA matrix computed from Bray-Curtis.