classify-hybrid-vsearch-sklearn: ALPHA Hybrid classifier: VSEARCH exact match + sklearn classifier¶

Docstring:

Usage: qiime feature-classifier classify-hybrid-vsearch-sklearn
           [OPTIONS]

  NOTE: THIS PIPELINE IS AN ALPHA RELEASE. Please report bugs to
  https://forum.qiime2.org! Assign taxonomy to query sequences using hybrid
  classifier. First performs rough positive filter to remove artifact and low-
  coverage sequences (use "prefilter" parameter to toggle this step on or
  off). Second, performs VSEARCH exact match between query and reference_reads
  to find exact matches, followed by least common ancestor consensus taxonomy
  assignment from among maxaccepts top hits, min_consensus of which share that
  taxonomic assignment. Query sequences without an exact match are then
  classified with a pre-trained sklearn taxonomy classifier to predict the
  most likely taxonomic lineage.

Inputs:
  --i-query ARTIFACT FeatureData[Sequence]
                        Query Sequences.                            [required]
  --i-reference-reads ARTIFACT FeatureData[Sequence]
                        Reference sequences.                        [required]
  --i-reference-taxonomy ARTIFACT FeatureData[Taxonomy]
                        Reference taxonomy labels.                  [required]
  --i-classifier ARTIFACT TaxonomicClassifier
                        Pre-trained sklearn taxonomic classifier for
                        classifying the reads.                      [required]
Parameters:
  --p-maxaccepts VALUE Int % Range(1, None) | Str % Choices('all')
                        Maximum number of hits to keep for each query. Set to
                        "all" to keep all hits > perc-identity similarity.
                        Note that if strand=both, maxaccepts will keep N hits
                        for each direction (if searches in the opposite
                        direction yield results that exceed the minimum
                        perc-identity). In those cases use maxhits to control
                        the total number of hits returned. This option works
                        in pair with maxrejects. The search process sorts
                        target sequences by decreasing number of k-mers they
                        have in common with the query sequence, using that
                        information as a proxy for sequence similarity. After
                        pairwise alignments, if the first target sequence
                        passes the acceptation criteria, it is accepted as
                        best hit and the search process stops for that query.
                        If maxaccepts is set to a higher value, more hits are
                        accepted. If maxaccepts and maxrejects are both set to
                        "all", the complete database is searched.
                                                                 [default: 10]
  --p-perc-identity PROPORTION Range(0.0, 1.0, inclusive_end=True)
                        Percent sequence similarity to use for PREFILTER.
                        Reject match if percent identity to query is lower.
                        Set to a lower value to perform a rough pre-filter.
                        This parameter is ignored if `prefilter` is disabled.
                                                                [default: 0.5]
  --p-query-cov PROPORTION Range(0.0, 1.0, inclusive_end=True)
                        Query coverage threshold to use for PREFILTER. Reject
                        match if query alignment coverage per high-scoring
                        pair is lower. Set to a lower value to perform a rough
                        pre-filter. This parameter is ignored if `prefilter`
                        is disabled.                            [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.   [default: 0.51]
  --p-maxhits VALUE Int % Range(1, None) | Str % Choices('all')
                                                              [default: 'all']
  --p-maxrejects VALUE Int % Range(1, None) | Str % Choices('all')
                                                              [default: 'all']
  --p-reads-per-batch VALUE Int % Range(1, None) | Str % Choices('auto')
                        Number of reads to process in each batch for sklearn
                        classification. If "auto", this parameter is
                        autoscaled to min(number of query sequences / threads,
                        20000).                              [default: 'auto']
  --p-confidence VALUE Float % Range(0, 1, inclusive_end=True) | Str %
    Choices('disable')  Confidence threshold for limiting taxonomic depth.
                        Set to "disable" to disable confidence calculation, or
                        0 to calculate confidence but not apply it to limit
                        the taxonomic depth of the assignments. [default: 0.7]
  --p-read-orientation TEXT Choices('same', 'reverse-complement', 'auto')
                        Direction of reads with respect to reference
                        sequences in pre-trained sklearn classifier. same will
                        cause reads to be classified unchanged;
                        reverse-complement will cause reads to be reversed and
                        complemented prior to classification. "auto" will
                        autodetect orientation based on the confidence
                        estimates for the first 100 reads.   [default: 'auto']
  --p-threads INTEGER   Number of threads to use for job parallelization.
    Range(1, None)                                                [default: 1]
  --p-prefilter / --p-no-prefilter
                        Toggle positive filter of query sequences on or off.
                                                               [default: True]
  --p-sample-size INTEGER
    Range(1, None)      Randomly extract the given number of sequences from
                        the reference database to use for prefiltering. This
                        parameter is ignored if `prefilter` is disabled.
                                                               [default: 1000]
  --p-randseed INTEGER  Use integer as a seed for the pseudo-random generator
    Range(0, None)      used during prefiltering. A given seed always produces
                        the same output, which is useful for replicability.
                        Set to 0 to use a pseudo-random seed. This parameter
                        is ignored if `prefilter` is disabled.    [default: 0]
Outputs:
  --o-classification ARTIFACT FeatureData[Taxonomy]
                        Taxonomy classifications of query sequences.
                                                                    [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.