annotate qiime2/qiime_sample-classifier_scatterplot.xml @ 9:f190567fe3f6 draft

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author florianbegusch
date Wed, 14 Aug 2019 15:12:48 -0400
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1 <?xml version="1.0" ?>
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2 <tool id="qiime_sample-classifier_scatterplot" name="qiime sample-classifier scatterplot" version="2019.7">
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3 <description> - Make 2D scatterplot and linear regression of regressor predictions.</description>
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4 <requirements>
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5 <requirement type="package" version="2019.7">qiime2</requirement>
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6 </requirements>
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7 <command><![CDATA[
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8 qiime sample-classifier scatterplot
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10 --i-predictions=$ipredictions
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11 --m-truth-column="$mtruthcolumn"
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13 --m-truth-file="$mtruthfile"
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15 #if str($pmissingsamples) != 'None':
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16 --p-missing-samples=$pmissingsamples
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17 #end if
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18
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19 --o-visualization=ovisualization
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20 ;
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21 qiime tools export --input-path ovisualization.qzv --output-path out && mkdir -p '$ovisualization.files_path'
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22 && cp -r out/* '$ovisualization.files_path'
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23 && mv '$ovisualization.files_path/index.html' '$ovisualization';
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24 ]]></command>
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25 <inputs>
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26 <param format="qza,no_unzip.zip" label="--i-predictions: ARTIFACT SampleData[RegressorPredictions] Predicted values to plot on y axis. Must be predictions of numeric data produced by a sample regressor. [required]" name="ipredictions" optional="False" type="data"/>
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27 <param label="--m-truth-column: COLUMN MetadataColumn[Numeric] Metadata column (true values) to plot on x axis. [required]" name="mtruthcolumn" optional="False" type="text"/>
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28 <param label="--p-missing-samples: " name="pmissingsamples" optional="True" type="select">
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29 <option selected="True" value="None">Selection is Optional</option>
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30 <option value="error">error</option>
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31 <option value="ignore">ignore</option>
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32 </param>
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33
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34 <param label="--m-truth-file: Metadata file or artifact viewable as metadata." name="mtruthfile" type="data" format="tabular,qza,no_unzip.zip" />
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35
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36 </inputs>
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37 <outputs>
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38 <data format="html" label="${tool.name} on ${on_string}: visualization.qzv" name="ovisualization"/>
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39 </outputs>
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40 <help><![CDATA[
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41 Make 2D scatterplot and linear regression of regressor predictions.
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42 ###################################################################
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43
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44 Make a 2D scatterplot and linear regression of predicted vs. true values
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45 for a set of samples predicted using a sample regressor.
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46
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47 Parameters
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48 ----------
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49 predictions : SampleData[RegressorPredictions]
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50 Predicted values to plot on y axis. Must be predictions of numeric data
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51 produced by a sample regressor.
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52 truth : MetadataColumn[Numeric]
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53 Metadata column (true values) to plot on x axis.
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54 missing_samples : Str % Choices('error', 'ignore'), optional
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55 How to handle missing samples in metadata. "error" will fail if missing
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56 samples are detected. "ignore" will cause the feature table and
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57 metadata to be filtered, so that only samples found in both files are
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58 retained.
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59
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60 Returns
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61 -------
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62 visualization : Visualization
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63 ]]></help>
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64 <macros>
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65 <import>qiime_citation.xml</import>
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66 </macros>
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67 <expand macro="qiime_citation"/>
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68 </tool>