Docstring:
Usage: qiime diversity core-metrics-phylogenetic [OPTIONS]
Applies a collection of diversity metrics (both phylogenetic and non-
phylogenetic) to a feature table.
Inputs:
--i-table ARTIFACT FeatureTable[Frequency]
The feature table containing the samples over which
diversity metrics 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-sampling-depth INTEGER
Range(1, None) The total frequency that each sample should be
rarefied to prior to computing diversity metrics.
[required]
--m-metadata-file METADATA...
(multiple arguments The sample metadata to use in the emperor plots.
will be merged) [required]
--p-with-replacement / --p-no-with-replacement
Rarefy with replacement by sampling from the
multinomial distribution instead of rarefying
without replacement. [default: False]
--p-n-jobs-or-threads NTHREADS
[beta/beta-phylogenetic methods only] - The number
of concurrent jobs or CPU threads to use in
performing this calculation. Individual methods will
create jobs/threads as implemented in
q2-diversity-lib dependencies. May not exceed the
number of available physical cores. If
n-jobs-or-threads = 'auto', one thread/job will be
created for each identified CPU core on the host.
[default: 1]
--p-ignore-missing-samples / --p-no-ignore-missing-samples
If set to `True` samples and features without
metadata are included by setting all metadata values
to: "This element has no metadata". By default an
exception will be raised if missing elements are
encountered. Note, this flag only takes effect if
there is at least one overlapping element.
[default: False]
Outputs:
--o-rarefied-table ARTIFACT FeatureTable[Frequency]
The resulting rarefied feature table. [required]
--o-faith-pd-vector ARTIFACT SampleData[AlphaDiversity]
Vector of Faith PD values by sample. [required]
--o-observed-features-vector ARTIFACT SampleData[AlphaDiversity]
Vector of Observed Features values by sample.
[required]
--o-shannon-vector ARTIFACT SampleData[AlphaDiversity]
Vector of Shannon diversity values by sample.
[required]
--o-evenness-vector ARTIFACT SampleData[AlphaDiversity]
Vector of Pielou's evenness values by sample.
[required]
--o-unweighted-unifrac-distance-matrix ARTIFACT
DistanceMatrix Matrix of unweighted UniFrac distances between
pairs of samples. [required]
--o-weighted-unifrac-distance-matrix ARTIFACT
DistanceMatrix Matrix of weighted UniFrac distances between pairs
of samples. [required]
--o-jaccard-distance-matrix ARTIFACT
DistanceMatrix Matrix of Jaccard distances between pairs of
samples. [required]
--o-bray-curtis-distance-matrix ARTIFACT
DistanceMatrix Matrix of Bray-Curtis distances between pairs of
samples. [required]
--o-unweighted-unifrac-pcoa-results ARTIFACT
PCoAResults PCoA matrix computed from unweighted UniFrac
distances between samples. [required]
--o-weighted-unifrac-pcoa-results ARTIFACT
PCoAResults PCoA matrix computed from weighted UniFrac
distances between samples. [required]
--o-jaccard-pcoa-results ARTIFACT
PCoAResults PCoA matrix computed from Jaccard distances between
samples. [required]
--o-bray-curtis-pcoa-results ARTIFACT
PCoAResults PCoA matrix computed from Bray-Curtis distances
between samples. [required]
--o-unweighted-unifrac-emperor VISUALIZATION
Emperor plot of the PCoA matrix computed from
unweighted UniFrac. [required]
--o-weighted-unifrac-emperor VISUALIZATION
Emperor plot of the PCoA matrix computed from
weighted UniFrac. [required]
--o-jaccard-emperor VISUALIZATION
Emperor plot of the PCoA matrix computed from
Jaccard. [required]
--o-bray-curtis-emperor VISUALIZATION
Emperor plot of the PCoA matrix computed from
Bray-Curtis. [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).
--recycle-pool TEXT Use a cache pool for pipeline resumption. QIIME 2
will cache your results in this pool for reuse by
future invocations. These pool are retained until
deleted by the user. If not provided, QIIME 2 will
create a pool which is automatically reused by
invocations of the same action and removed if the
action is successful. Note: these pools are local to
the cache you are using.
--no-recycle Do not recycle results from a previous failed
pipeline run or save the results from this run for
future recycling.
--parallel Execute your action in parallel. This flag will use
your default parallel config.
--parallel-config FILE Execute your action in parallel using a config at
the indicated path.
--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.
Import:
from qiime2.plugins.diversity.pipelines import core_metrics_phylogenetic
Docstring:
Core diversity metrics (phylogenetic and non-phylogenetic)
Applies a collection of diversity metrics (both phylogenetic and non-
phylogenetic) to a feature table.
Parameters
----------
table : FeatureTable[Frequency]
The feature table containing the samples over which diversity metrics
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.
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.
with_replacement : Bool, optional
Rarefy with replacement by sampling from the multinomial distribution
instead of rarefying without replacement.
n_jobs_or_threads : Threads, optional
[beta/beta-phylogenetic methods only] - The number of concurrent jobs
or CPU threads to use in performing this calculation. Individual
methods will create jobs/threads as implemented in q2-diversity-lib
dependencies. May not exceed the number of available physical cores. If
n_jobs_or_threads = 'auto', one thread/job will be created for each
identified CPU core on the host.
ignore_missing_samples : Bool, optional
If set to `True` samples and features without metadata are included by
setting all metadata values to: "This element has no metadata". By
default an exception will be raised if missing elements are
encountered. Note, this flag only takes effect if there is at least one
overlapping element.
Returns
-------
rarefied_table : FeatureTable[Frequency]
The resulting rarefied feature table.
faith_pd_vector : SampleData[AlphaDiversity]
Vector of Faith PD values by sample.
observed_features_vector : SampleData[AlphaDiversity]
Vector of Observed Features 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.
unweighted_unifrac_distance_matrix : DistanceMatrix
Matrix of unweighted UniFrac distances between pairs of samples.
weighted_unifrac_distance_matrix : DistanceMatrix
Matrix of weighted UniFrac distances between pairs of samples.
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.
unweighted_unifrac_pcoa_results : PCoAResults
PCoA matrix computed from unweighted UniFrac distances between samples.
weighted_unifrac_pcoa_results : PCoAResults
PCoA matrix computed from weighted UniFrac distances between 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.
unweighted_unifrac_emperor : Visualization
Emperor plot of the PCoA matrix computed from unweighted UniFrac.
weighted_unifrac_emperor : Visualization
Emperor plot of the PCoA matrix computed from weighted UniFrac.
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.
