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1 <?xml version="1.0" ?>
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2 <tool id="qiime_feature-classifier_classify-sklearn" name="qiime feature-classifier classify-sklearn"
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3 version="2020.8">
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4 <description>Pre-fitted sklearn-based taxonomy classifier</description>
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5 <requirements>
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6 <requirement type="package" version="2020.8">qiime2</requirement>
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7 </requirements>
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8 <command><![CDATA[
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9 qiime feature-classifier classify-sklearn
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10
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11 --i-reads=$ireads
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12
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13 --i-classifier=$iclassifier
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14
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15 --p-n-jobs=$pnjobs
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16
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17 #if str($pconfidence) != 'None':
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18 --p-confidence=$pconfidence
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19 #end if
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20
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21 #if str($preadorientation) != 'None':
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22 --p-read-orientation=$preadorientation
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23 #end if
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24
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25 --o-classification=oclassification
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26
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27 #if str($examples) != 'None':
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28 --examples=$examples
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29 #end if
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30
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31 ;
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32 cp oclassification.qza $oclassification
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33
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34 ]]></command>
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35 <inputs>
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36 <param format="qza,no_unzip.zip" label="--i-reads: ARTIFACT FeatureData[Sequence] The feature data to be classified. [required]" name="ireads" optional="False" type="data" />
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37 <param format="qza,no_unzip.zip" label="--i-classifier: ARTIFACT TaxonomicClassifier The taxonomic classifier for classifying the reads. [required]" name="iclassifier" optional="False" type="data" />
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38 <param label="--p-confidence: " name="pconfidence" optional="True" type="select">
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39 <option selected="True" value="None">Selection is Optional</option>
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40 <option value="Float % Range(0">Float % Range(0</option>
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41 <option value="1">1</option>
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42 <option value="inclusive_end=True">inclusive_end=True</option>
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43 </param>
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44 <param label="--p-read-orientation: " name="preadorientation" optional="True" type="select">
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45 <option selected="True" value="None">Selection is Optional</option>
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46 <option value="same">same</option>
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47 <option value="reverse-complement">reverse-complement</option>
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48 <option value="auto">auto</option>
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49 </param>
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50 <param label="--examples: Show usage examples and exit." name="examples" optional="False" type="data" />
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51
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52 </inputs>
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53
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54 <outputs>
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55 <data format="qza" label="${tool.name} on ${on_string}: classification.qza" name="oclassification" />
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56
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57 </outputs>
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58
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59 <help><![CDATA[
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60 Pre-fitted sklearn-based taxonomy classifier
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61 ###############################################################
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62
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63 Classify reads by taxon using a fitted classifier.
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64
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65 Parameters
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66 ----------
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67 reads : FeatureData[Sequence]
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68 The feature data to be classified.
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69 classifier : TaxonomicClassifier
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70 The taxonomic classifier for classifying the reads.
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71 reads_per_batch : Int % Range(0, None), optional
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72 Number of reads to process in each batch. If "auto", this parameter is
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73 autoscaled to min( number of query sequences / n_jobs, 20000).
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74 n_jobs : Int, optional
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75 The maximum number of concurrently worker processes. If -1 all CPUs are
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76 used. If 1 is given, no parallel computing code is used at all, which
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77 is useful for debugging. For n_jobs below -1, (n_cpus + 1 + n_jobs) are
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78 used. Thus for n_jobs = -2, all CPUs but one are used.
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79 pre_dispatch : Str, optional
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80 "all" or expression, as in "3*n_jobs". The number of batches (of tasks)
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81 to be pre-dispatched.
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82 confidence : Float % Range(0, 1, inclusive_end=True) | Str % Choices('disable'), optional
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83 Confidence threshold for limiting taxonomic depth. Set to "disable" to
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84 disable confidence calculation, or 0 to calculate confidence but not
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85 apply it to limit the taxonomic depth of the assignments.
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86 read_orientation : Str % Choices('same', 'reverse-complement', 'auto'), optional
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87 Direction of reads with respect to reference sequences. same will cause
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88 reads to be classified unchanged; reverse-complement will cause reads
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89 to be reversed and complemented prior to classification. "auto" will
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90 autodetect orientation based on the confidence estimates for the first
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91 100 reads.
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92
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93 Returns
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94 -------
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95 classification : FeatureData[Taxonomy]
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96 ]]></help>
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97 <macros>
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98 <import>qiime_citation.xml</import>
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99 </macros>
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100 <expand macro="qiime_citation"/>
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101 </tool> |
