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filter-features-conditionally: Filter features from a table based on abundance and prevalence

Docstring:

Usage: qiime feature-table filter-features-conditionally [OPTIONS]

  Filter features based on the relative abundance in a certain portion of
  samples (i.e., features must have a relative abundance of at least
  `abundance` in at least `prevalence` number of samples). Any samples with a
  frequency of zero after feature filtering will also be removed.

Inputs:
  --i-table ARTIFACT FeatureTable[Frequency¹ | RelativeFrequency² |
    PresenceAbsence³ | Composition⁴]
                         The feature table from which features should be
                         filtered.                                  [required]
Parameters:
  --p-abundance PROPORTION
    Range(0, 1)          The minimum relative abundance for a feature to be
                         retained.                                  [required]
  --p-prevalence PROPORTION
    Range(0, 1)          The minimum portion of samples that a feature must
                         have a relative abundance of at least `abundance` to
                         be retained.                               [required]
  --p-allow-empty-table / --p-no-allow-empty-table
                         If true, the filtered table may be empty. Default
                         behavior is to raise an error if the filtered table
                         is empty.                            [default: False]
Outputs:
  --o-filtered-table ARTIFACT FeatureTable[Frequency¹ | RelativeFrequency²
    | PresenceAbsence³ | Composition⁴]
                         The resulting feature table filtered by feature.
                                                                    [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: feature table filter features conditionally
  # Retain only features with at least 1%% abundance in at least 34%% of
  # samples.
  qiime feature-table filter-features-conditionally \
    --i-table feature-table.qza \
    --p-abundance 0.01 \
    --p-prevalence 0.34 \
    --o-filtered-table filtered-table.qza

Import:

from qiime2.plugins.feature_table.methods import filter_features_conditionally

Docstring:

Filter features from a table based on abundance and prevalence

Filter features based on the relative abundance in a certain portion of
samples (i.e., features must have a relative abundance of at least
`abundance` in at least `prevalence` number of samples). Any samples with a
frequency of zero after feature filtering will also be removed.

Parameters
----------
table : FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]
    The feature table from which features should be filtered.
abundance : Float % Range(0, 1)
    The minimum relative abundance for a feature to be retained.
prevalence : Float % Range(0, 1)
    The minimum portion of samples that a feature must have a relative
    abundance of at least `abundance` to be retained.
allow_empty_table : Bool, optional
    If true, the filtered table may be empty. Default behavior is to raise
    an error if the filtered table is empty.

Returns
-------
filtered_table : FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]
    The resulting feature table filtered by feature.