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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" version="2019.4">
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3 <description> - Pre-fitted sklearn-based taxonomy classifier</description>
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4 <requirements>
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5 <requirement type="package" version="2019.4">qiime2</requirement>
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6 </requirements>
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7 <command><![CDATA[
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8 qiime feature-classifier classify-sklearn
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9
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10 --i-reads=$ireads
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11 --i-classifier=$iclassifier
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12
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13 #set $pnjobs = '${GALAXY_SLOTS:-4}'
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14
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15 #if str($pnjobs):
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16 --p-n-jobs="$pnjobs"
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17 #end if
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18
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19
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20 #if $pconfidence:
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21 --p-confidence=$pconfidence
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22 #end if
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23
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24 #if str($preadorientation) != 'None':
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25 --p-read-orientation=$preadorientation
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26 #end if
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27
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28 --o-classification=oclassification
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29 ;
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30 cp oclassification.qza $oclassification
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31 ]]></command>
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32 <inputs>
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33 <param format="qza,no_unzip.zip" label="--i-reads: ARTIFACT FeatureData[Sequence] The feature data to be classified. [required]" name="ireads" optional="False" type="data"/>
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34 <param format="qza,no_unzip.zip" label="--i-classifier: ARTIFACT TaxonomicClassifier The taxonomic classifier for classifying the reads. [required]" name="iclassifier" optional="False" type="data"/>
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35 <param label="--p-confidence: NUMBER Confidence threshold for limiting taxonomic depth. Provide -1 to disable confidence calculation, or 0 to calculate confidence but not apply it to limit the taxonomic depth of the assignments. [default: 0.7]" name="pconfidence" optional="True" type="float" value="0.7"/>
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36 <param label="--p-read-orientation: " name="preadorientation" optional="True" type="select">
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37 <option selected="True" value="None">Selection is Optional</option>
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38 <option value="same">same</option>
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39 <option value="reverse-complement">reverse-complement</option>
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40 </param>
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41 </inputs>
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42 <outputs>
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43 <data format="qza" label="${tool.name} on ${on_string}: classification.qza" name="oclassification"/>
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44 </outputs>
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45 <help><![CDATA[
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46 Pre-fitted sklearn-based taxonomy classifier
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47 ############################################
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48
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49 Classify reads by taxon using a fitted classifier.
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50
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51 Parameters
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52 ----------
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53 reads : FeatureData[Sequence]
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54 The feature data to be classified.
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55 classifier : TaxonomicClassifier
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56 The taxonomic classifier for classifying the reads.
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57 reads_per_batch : Int % Range(0, None), optional
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58 Number of reads to process in each batch. If 0, this parameter is
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59 autoscaled to min( number of query sequences / n_jobs, 20000).
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60 pre_dispatch : Str, optional
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61 "all" or expression, as in "3*n_jobs". The number of batches (of tasks)
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62 to be pre-dispatched.
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63 confidence : Float, optional
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64 Confidence threshold for limiting taxonomic depth. Provide -1 to
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65 disable confidence calculation, or 0 to calculate confidence but not
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66 apply it to limit the taxonomic depth of the assignments.
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67 read_orientation : Str % Choices('same', 'reverse-complement'), optional
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68 Direction of reads with respect to reference sequences. same will cause
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69 reads to be classified unchanged; reverse-complement will cause reads
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70 to be reversed and complemented prior to classification. Default is to
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71 autodetect based on the confidence estimates for the first 100 reads.
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72
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73 Returns
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74 -------
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75 classification : FeatureData[Taxonomy]
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76 ]]></help>
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77 <macros>
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78 <import>qiime_citation.xml</import>
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79 </macros>
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80 <expand macro="qiime_citation"/>
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81 </tool>
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