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evaluate-classifications: Interactively evaluate taxonomic classification accuracy.

Citations
  • Nicholas A. Bokulich, Matthew R. Dillon, Yilong Zhang, Jai Ram Rideout, Evan Bolyen, Huilin Li, Paul S. Albert, and J. Gregory Caporaso. Q2-longitudinal: longitudinal and paired-sample analyses of microbiome data. mSystems, 3(6):e00219–18, 2018. doi:10.1128/mSystems.00219-18.

  • Nicholas A. Bokulich, Benjamin D. Kaehler, Jai Ram Rideout, Matthew Dillon, Evan Bolyen, Rob Knight, Gavin A. Huttley, and J. Gregory Caporaso. Optimizing taxonomic classification of marker-gene amplicon sequences with qiime 2's q2-feature-classifier plugin. Microbiome, 6(1):90, 2018. URL: https://doi.org/10.1186/s40168-018-0470-z, doi:10.1186/s40168-018-0470-z.

Docstring:

Usage: qiime rescript evaluate-classifications [OPTIONS]

  Evaluate taxonomic classification accuracy by comparing one or more sets of
  true taxonomic labels to the predicted taxonomies for the same set(s) of
  features. Output an interactive line plot of classification accuracy for
  each pair of expected/observed taxonomies. The x-axis in these plots
  represents the taxonomic levels present in the input taxonomies so are
  labeled numerically instead of by rank, but typically for 7-level taxonomies
  these will represent: 1 = domain/kingdom, 2 = phylum, 3 = class, 4 = order,
  5 = family, 6 = genus, 7 = species.

Inputs:
  --i-expected-taxonomies ARTIFACTS... List[FeatureData[Taxonomy]]
                          True taxonomic labels for one more more sets of
                          features.                                 [required]
  --i-observed-taxonomies ARTIFACTS... List[FeatureData[Taxonomy]]
                          Predicted classifications of same sets of features,
                          input in same order as expected-taxonomies.
                                                                    [required]
Parameters:
  --p-labels TEXT...      List of labels to use for labeling evaluation
    List[Str]             results in the resulting visualization. Inputs are
                          labeled with labels in the order that each is input.
                          If there are fewer labels than inputs (or no
                          labels), unnamed inputs are labeled numerically in
                          sequential order. Extra labels are ignored.
                                                                    [optional]
Outputs:
  --o-evaluation VISUALIZATION
                          Visualization of classification accuracy results.
                                                                    [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).
  --recycle-pool TEXT     Use a cache pool for pipeline resumption. QIIME 2
                          will cache your results in this pool for reuse by
                          future invocations. These pool are retained until
                          deleted by the user. If not provided, QIIME 2 will
                          create a pool which is automatically reused by
                          invocations of the same action and removed if the
                          action is successful. Note: these pools are local to
                          the cache you are using.
  --no-recycle            Do not recycle results from a previous failed
                          pipeline run or save the results from this run for
                          future recycling.
  --parallel              Execute your action in parallel. This flag will use
                          your default parallel config.
  --parallel-config FILE  Execute your action in parallel using a config at
                          the indicated path.
  --use-cache DIRECTORY   Specify the cache to be used for the intermediate
                          work of this pipeline. 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.
  --example-data PATH     Write example data and exit.
  --citations             Show citations and exit.
  --help                  Show this message and exit.

Import:

from qiime2.plugins.rescript.pipelines import evaluate_classifications

Docstring:

Interactively evaluate taxonomic classification accuracy.

Evaluate taxonomic classification accuracy by comparing one or more sets of
true taxonomic labels to the predicted taxonomies for the same set(s) of
features. Output an interactive line plot of classification accuracy for
each pair of expected/observed taxonomies. The x-axis in these plots
represents the taxonomic levels present in the input taxonomies so are
labeled numerically instead of by rank, but typically for 7-level
taxonomies these will represent: 1 = domain/kingdom, 2 = phylum, 3 = class,
4 = order, 5 = family, 6 = genus, 7 = species.

Parameters
----------
expected_taxonomies : List[FeatureData[Taxonomy]]
    True taxonomic labels for one more more sets of features.
observed_taxonomies : List[FeatureData[Taxonomy]]
    Predicted classifications of same sets of features, input in same order
    as expected_taxonomies.
labels : List[Str], optional
    List of labels to use for labeling evaluation results in the resulting
    visualization. Inputs are labeled with labels in the order that each is
    input. If there are fewer labels than inputs (or no labels), unnamed
    inputs are labeled numerically in sequential order. Extra labels are
    ignored.

Returns
-------
evaluation : Visualization
    Visualization of classification accuracy results.