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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"
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3 version="2020.8">
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4 <description>Make 2D scatterplot and linear regression of regressor predictions.</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 scatterplot
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10
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11 --i-predictions=$ipredictions
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12
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13 #if str($mtruthfile) != 'None':
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14 --m-truth-file=$mtruthfile
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15 #end if
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16
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17 #if '__ob__' in str($mtruthcolumn):
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18 #set $mtruthcolumn_temp = $mtruthcolumn.replace('__ob__', '[')
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19 #set $mtruthcolumn = $mtruthcolumn_temp
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20 #end if
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21 #if '__cb__' in str($mtruthcolumn):
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22 #set $mtruthcolumn_temp = $mtruthcolumn.replace('__cb__', ']')
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23 #set $mtruthcolumn = $mtruthcolumn_temp
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24 #end if
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25 #if 'X' in str($mtruthcolumn):
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26 #set $mtruthcolumn_temp = $mtruthcolumn.replace('X', '\\')
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27 #set $mtruthcolumn = $mtruthcolumn_temp
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28 #end if
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29 #if '__sq__' in str($mtruthcolumn):
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30 #set $mtruthcolumn_temp = $mtruthcolumn.replace('__sq__', "'")
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31 #set $mtruthcolumn = $mtruthcolumn_temp
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32 #end if
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33 #if '__db__' in str($mtruthcolumn):
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34 #set $mtruthcolumn_temp = $mtruthcolumn.replace('__db__', '"')
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35 #set $mtruthcolumn = $mtruthcolumn_temp
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36 #end if
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37
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38 --m-truth-column=$mtruthcolumn
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39
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40
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41 #if str($pmissingsamples) != 'None':
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42 --p-missing-samples=$pmissingsamples
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43 #end if
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44
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45 --o-visualization=ovisualization
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46
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47 #if str($examples) != 'None':
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48 --examples=$examples
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49 #end if
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50
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51 ;
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52 cp ofeatureimportance.qza $ofeatureimportance
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53
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54 ;
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55 qiime tools export ovisualization.qzv --output-path out
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56 && mkdir -p '$ovisualization.files_path'
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57 && cp -r out/* '$ovisualization.files_path'
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58 && mv '$ovisualization.files_path/index.html' '$ovisualization'
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59
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60 ]]></command>
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61 <inputs>
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62 <param format="qza,no_unzip.zip" label="--i-predictions: ARTIFACT SampleData[RegressorPredictions] Predicted values to plot on y axis. Must be predictions of numeric data produced by a sample regressor. [required]" name="ipredictions" optional="False" type="data" />
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63 <param label="--m-truth-file: METADATA" name="mtruthfile" optional="False" type="data" />
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64 <param label="--m-truth-column: COLUMN MetadataColumn[Numeric] Metadata column (true values) to plot on x axis. [required]" name="mtruthcolumn" optional="False" type="text" />
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65 <param label="--p-missing-samples: " name="pmissingsamples" optional="True" type="select">
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66 <option selected="True" value="None">Selection is Optional</option>
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67 <option value="error">error</option>
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68 <option value="ignore">ignore</option>
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69 </param>
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70 <param label="--examples: Show usage examples and exit." name="examples" optional="False" type="data" />
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71
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72 </inputs>
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73
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74 <outputs>
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75 <data format="html" label="${tool.name} on ${on_string}: visualization.html" name="ovisualization" />
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76
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77 </outputs>
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78
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79 <help><![CDATA[
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80 Make 2D scatterplot and linear regression of regressor predictions.
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81 ###############################################################
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82
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83 Make a 2D scatterplot and linear regression of predicted vs. true values
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84 for a set of samples predicted using a sample regressor.
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85
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86 Parameters
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87 ----------
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88 predictions : SampleData[RegressorPredictions]
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89 Predicted values to plot on y axis. Must be predictions of numeric data
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90 produced by a sample regressor.
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91 truth : MetadataColumn[Numeric]
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92 Metadata column (true values) to plot on x axis.
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93 missing_samples : Str % Choices('error', 'ignore'), optional
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94 How to handle missing samples in metadata. "error" will fail if missing
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95 samples are detected. "ignore" will cause the feature table and
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96 metadata to be filtered, so that only samples found in both files are
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97 retained.
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98
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99 Returns
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100 -------
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101 visualization : Visualization
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102 ]]></help>
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103 <macros>
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104 <import>qiime_citation.xml</import>
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105 </macros>
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106 <expand macro="qiime_citation"/>
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107 </tool> |
