annotate qiime2/qiime_sample-classifier_split-table.xml @ 13:887cd4ad8e16 draft

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author florianbegusch
date Thu, 03 Sep 2020 09:46:00 +0000
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1 <?xml version="1.0" ?>
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2 <tool id="qiime_sample-classifier_split-table" name="qiime sample-classifier split-table" version="2019.7">
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3 <description> - Split a feature table into training and testing sets.</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 split-table
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10 --i-table=$itable
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11 --m-metadata-column="$mmetadatacolumn"
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12
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15 #if $metadatafile:
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16 --m-metadata-file=$metadatafile
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17 #end if
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19
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21
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22 #if str($ptestsize):
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23 --p-test-size=$ptestsize
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24 #end if
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25
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26 #if str($prandomstate):
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27 --p-random-state="$prandomstate"
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28 #end if
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29
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30 #if $pnostratify:
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31 --p-no-stratify
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32 #end if
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33
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34 #if str($pmissingsamples) != 'None':
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35 --p-missing-samples=$pmissingsamples
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36 #end if
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37
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38 --o-training-table=otrainingtable
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39 --o-test-table=otesttable
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40 ;
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41 cp otrainingtable.qza $otrainingtable;
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42 cp otesttable.qza $otesttable;
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43 ]]></command>
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44 <inputs>
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45 <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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46 <param label="--m-metadata-column: COLUMN MetadataColumn[Numeric | Categorical] Numeric metadata column to use as prediction target. [required]" name="mmetadatacolumn" optional="False" type="text"/>
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47 <param label="--p-test-size: PROPORTION Range(0.0, 1.0, inclusive_start=False) Fraction of input samples to exclude from training set and use for classifier testing. [default: 0.2]" name="ptestsize" optional="True" type="float" value="0.2" min="0" max="1" exclusive_end="True"/>
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48 <param label="--p-random-state: INTEGER Seed used by random number generator. [optional]" name="prandomstate" optional="True" type="integer"/>
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49 <param label="--p-no-stratify: Evenly stratify training and test data among metadata categories. If True, all values in column must match at least two samples. [default: False]" name="pnostratify" selected="False" type="boolean"/>
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50 <param label="--p-missing-samples: " name="pmissingsamples" optional="True" type="select">
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51 <option selected="True" value="None">Selection is Optional</option>
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52 <option value="error">error</option>
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53 <option value="ignore">ignore</option>
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54 </param>
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55
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56 <param label="--m-metadata-file METADATA" name="metadatafile" type="data" format="tabular,qza,no_unzip.zip" />
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58 </inputs>
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59 <outputs>
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60 <data format="qza" label="${tool.name} on ${on_string}: trainingtable.qza" name="otrainingtable"/>
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61 <data format="qza" label="${tool.name} on ${on_string}: testtable.qza" name="otesttable"/>
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62 </outputs>
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63 <help><![CDATA[
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64 Split a feature table into training and testing sets.
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65 #####################################################
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66
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67 Split a feature table into training and testing sets. By default stratifies
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68 training and test sets on a metadata column, such that values in that
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69 column are evenly represented across training and test sets.
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70
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71 Parameters
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72 ----------
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73 table : FeatureTable[Frequency]
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74 Feature table containing all features that should be used for target
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75 prediction.
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76 metadata : MetadataColumn[Numeric | Categorical]
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77 Numeric metadata column to use as prediction target.
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78 test_size : Float % Range(0.0, 1.0, inclusive_start=False), optional
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79 Fraction of input samples to exclude from training set and use for
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80 classifier testing.
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81 random_state : Int, optional
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82 Seed used by random number generator.
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83 stratify : Bool, optional
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84 Evenly stratify training and test data among metadata categories. If
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85 True, all values in column must match at least two samples.
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86 missing_samples : Str % Choices('error', 'ignore'), optional
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87 How to handle missing samples in metadata. "error" will fail if missing
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88 samples are detected. "ignore" will cause the feature table and
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89 metadata to be filtered, so that only samples found in both files are
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90 retained.
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91
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92 Returns
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93 -------
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94 training_table : FeatureTable[Frequency]
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95 Feature table containing training samples
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96 test_table : FeatureTable[Frequency]
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97 Feature table containing test samples
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98 ]]></help>
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99 <macros>
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100 <import>qiime_citation.xml</import>
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101 </macros>
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102 <expand macro="qiime_citation"/>
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103 </tool>