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find-consensus-annotation: Find consensus among multiple annotations.ΒΆ

Docstring:

Usage: qiime feature-classifier find-consensus-annotation [OPTIONS]

  Find consensus annotation for each query searched against a reference
  database, by finding the least common ancestor among one or more semicolon-
  delimited hierarchical annotations. Note that the annotation hierarchy is
  assumed to have an even number of ranks.

Inputs:
  --i-search-results ARTIFACT FeatureData[BLAST6]
                       Search results in BLAST6 output format       [required]
  --i-reference-taxonomy ARTIFACT FeatureData[Taxonomy]
                       reference taxonomy labels.                   [required]
Parameters:
  --p-min-consensus NUMBER Range(0.5, 1.0, inclusive_start=False,
    inclusive_end=True)
                       Minimum fraction of assignments must match top hit to
                       be accepted as consensus assignment.    [default: 0.51]
  --p-unassignable-label TEXT
                       Annotation given when no consensus is found.
                                                       [default: 'Unassigned']
Outputs:
  --o-consensus-taxonomy ARTIFACT FeatureData[Taxonomy]
                       Consensus taxonomy and scores.               [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.

Import:

from qiime2.plugins.feature_classifier.methods import find_consensus_annotation

Docstring:

Find consensus among multiple annotations.

Find consensus annotation for each query searched against a reference
database, by finding the least common ancestor among one or more semicolon-
delimited hierarchical annotations. Note that the annotation hierarchy is
assumed to have an even number of ranks.

Parameters
----------
search_results : FeatureData[BLAST6]
    Search results in BLAST6 output format
reference_taxonomy : FeatureData[Taxonomy]
    reference taxonomy labels.
min_consensus : Float % Range(0.5, 1.0, inclusive_start=False, inclusive_end=True), optional
    Minimum fraction of assignments must match top hit to be accepted as
    consensus assignment.
unassignable_label : Str, optional
    Annotation given when no consensus is found.

Returns
-------
consensus_taxonomy : FeatureData[Taxonomy]
    Consensus taxonomy and scores.