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.
--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.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.
