annotate qiime2/qiime_sample-classifier_predict-classification.xml @ 29:3ba9833030c1 draft

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author florianbegusch
date Fri, 04 Sep 2020 13:12:49 +0000
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1 <?xml version="1.0" ?>
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2 <tool id="qiime_sample-classifier_predict-classification" name="qiime sample-classifier predict-classification"
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3 version="2020.8">
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4 <description>Use trained classifier to predict target values for new samples.</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 sample-classifier predict-classification
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10
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11 --i-table=$itable
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12
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13 --i-sample-estimator=$isampleestimator
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14
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15 --p-n-jobs=$pnjobs
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16
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17 --o-predictions=opredictions
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18
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19 --o-probabilities=oprobabilities
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20
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21 #if str($examples) != 'None':
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22 --examples=$examples
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23 #end if
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24
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25 ;
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26 cp oprobabilities.qza $oprobabilities
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27
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28 ]]></command>
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29 <inputs>
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30 <param format="qza,no_unzip.zip" label="--i-table: ARTIFACT FeatureTable[Frequency] Feature table containing all features that should be used for target prediction. [required]" name="itable" optional="False" type="data" />
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31 <param format="qza,no_unzip.zip" label="--i-sample-estimator: ARTIFACT SampleEstimator[Classifier] Sample classifier trained with fit_classifier. [required]" name="isampleestimator" optional="False" type="data" />
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32 <param label="--examples: Show usage examples and exit." name="examples" optional="False" type="data" />
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33
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34 </inputs>
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35
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36 <outputs>
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37 <data format="qza" label="${tool.name} on ${on_string}: predictions.qza" name="opredictions" />
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38 <data format="qza" label="${tool.name} on ${on_string}: probabilities.qza" name="oprobabilities" />
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39
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40 </outputs>
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41
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42 <help><![CDATA[
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43 Use trained classifier to predict target values for new samples.
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44 ###############################################################
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45
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46 Use trained estimator to predict target values for new samples. These will
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47 typically be unseen samples, e.g., test data (derived manually or from
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48 split_table) or samples with unknown values, but can theoretically be any
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49 samples present in a feature table that contain overlapping features with
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50 the feature table used to train the estimator.
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51
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52 Parameters
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53 ----------
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54 table : FeatureTable[Frequency]
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55 Feature table containing all features that should be used for target
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56 prediction.
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57 sample_estimator : SampleEstimator[Classifier]
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58 Sample classifier trained with fit_classifier.
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59 n_jobs : Int, optional
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60 Number of jobs to run in parallel.
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61
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62 Returns
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63 -------
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64 predictions : SampleData[ClassifierPredictions]
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65 Predicted target values for each input sample.
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66 probabilities : SampleData[Probabilities]
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67 Predicted class probabilities for each input sample.
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68 ]]></help>
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69 <macros>
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70 <import>qiime_citation.xml</import>
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71 </macros>
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72 <expand macro="qiime_citation"/>
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73 </tool>