Fork me on GitHub

classify-consensus-vsearch: VSEARCH consensus taxonomy classifier

Citations
  • Torbjørn Rognes, Tomáš Flouri, Ben Nichols, Christopher Quince, and Frédéric Mahé. Vsearch: a versatile open source tool for metagenomics. PeerJ, 4:e2584, 2016. doi:10.7717/peerj.2584.

Docstring:

Usage: qiime feature-classifier classify-consensus-vsearch
           [OPTIONS]

  Assign taxonomy to query sequences using VSEARCH. Performs VSEARCH global
  alignment between query and reference_reads, then assigns consensus
  taxonomy to each query sequence from among maxaccepts top hits,
  min_consensus of which share that taxonomic assignment. Unlike classify-
  consensus-blast, this method searches the entire reference database before
  choosing the top N hits, not the first N hits.

Inputs:
  --i-query ARTIFACT FeatureData[Sequence]
                          Sequences to classify taxonomically.      [required]
  --i-reference-reads ARTIFACT FeatureData[Sequence]
                          reference sequences.                      [required]
  --i-reference-taxonomy ARTIFACT FeatureData[Taxonomy]
                          reference taxonomy labels.                [required]
Parameters:
  --p-maxaccepts INTEGER  Maximum number of hits to keep for each query. Set
    Range(0, None)        to 0 to keep all hits > perc-identity similarity.
                          Must be in range [0, infinity].        [default: 10]
  --p-perc-identity PROPORTION Range(0.0, 1.0, inclusive_end=True)
                          Reject match if percent identity to query is lower.
                          Must be in range [0.0, 1.0].          [default: 0.8]
  --p-query-cov PROPORTION Range(0.0, 1.0, inclusive_end=True)
                          Reject match if query alignment coverage per
                          high-scoring pair is lower. Must be in range [0.0,
                          1.0].                                 [default: 0.8]
  --p-strand TEXT Choices('both', 'plus')
                          Align against reference sequences in forward
                          ("plus") or both directions ("both").
                                                             [default: 'both']
  --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. Must be in
                          range (0.5, 1.0].                    [default: 0.51]
  --p-unassignable-label TEXT
                                                       [default: 'Unassigned']
  --p-threads INTEGER                                             [default: 1]
Outputs:
  --o-classification ARTIFACT FeatureData[Taxonomy]
                          The resulting taxonomy classifications.   [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).
  --citations             Show citations and exit.
  --help                  Show this message and exit.

Import:

from qiime2.plugins.feature_classifier.methods import classify_consensus_vsearch

Docstring:

VSEARCH consensus taxonomy classifier

Assign taxonomy to query sequences using VSEARCH. Performs VSEARCH global
alignment between query and reference_reads, then assigns consensus
taxonomy to each query sequence from among maxaccepts top hits,
min_consensus of which share that taxonomic assignment. Unlike classify-
consensus-blast, this method searches the entire reference database before
choosing the top N hits, not the first N hits.

Parameters
----------
query : FeatureData[Sequence]
    Sequences to classify taxonomically.
reference_reads : FeatureData[Sequence]
    reference sequences.
reference_taxonomy : FeatureData[Taxonomy]
    reference taxonomy labels.
maxaccepts : Int % Range(0, None), optional
    Maximum number of hits to keep for each query. Set to 0 to keep all
    hits > perc_identity similarity. Must be in range [0, infinity].
perc_identity : Float % Range(0.0, 1.0, inclusive_end=True), optional
    Reject match if percent identity to query is lower. Must be in range
    [0.0, 1.0].
query_cov : Float % Range(0.0, 1.0, inclusive_end=True), optional
    Reject match if query alignment coverage per high-scoring pair is
    lower. Must be in range [0.0, 1.0].
strand : Str % Choices('both', 'plus'), optional
    Align against reference sequences in forward ("plus") or both
    directions ("both").
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. Must be in range (0.5, 1.0].
unassignable_label : Str, optional
threads : Int, optional

Returns
-------
classification : FeatureData[Taxonomy]
    The resulting taxonomy classifications.