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1 <?xml version="1.0" ?>
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2 <tool id="qiime_sample-classifier_metatable" name="qiime sample-classifier metatable"
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3 version="2020.8">
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4 <description>Convert (and merge) positive numeric metadata (in)to feature table.</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 metatable
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10
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11 #if str($itable) != 'None':
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12 --i-table=$itable
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13 #end if
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14 # if $input_files_mmetadatafile:
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15 # def list_dict_to_string(list_dict):
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16 # set $file_list = list_dict[0]['additional_input'].__getattr__('file_name')
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17 # for d in list_dict[1:]:
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18 # set $file_list = $file_list + ' --m-metadata-file=' + d['additional_input'].__getattr__('file_name')
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19 # end for
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20 # return $file_list
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21 # end def
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22 --m-metadata-file=$list_dict_to_string($input_files_mmetadatafile)
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23 # end if
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24
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25 #if str($pmissingsamples) != 'None':
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26 --p-missing-samples=$pmissingsamples
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27 #end if
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28
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29 #if str($pmissingvalues) != 'None':
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30 --p-missing-values=$pmissingvalues
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31 #end if
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32
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33 #if $pdropallunique:
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34 --p-drop-all-unique
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35 #end if
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36
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37 --o-converted-table=oconvertedtable
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38
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39 #if str($examples) != 'None':
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40 --examples=$examples
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41 #end if
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42
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43 ;
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44 cp oconvertedtable.qza $oconvertedtable
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45
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46 ]]></command>
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47 <inputs>
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48 <param format="qza,no_unzip.zip" label="--i-table: ARTIFACT FeatureTable[Frequency] Feature table containing all features that should be used for target prediction. [optional]" name="itable" optional="False" type="data" />
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49 <repeat name="input_files_mmetadatafile" optional="False" title="--m-metadata-file">
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50 <param format="tabular,qza,no_unzip.zip" label="--m-metadata-file: METADATA... (multiple Metadata file to convert to feature table. arguments will be merged) [required]" name="additional_input" optional="False" type="data" />
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51 </repeat>
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52 <param label="--p-missing-samples: " name="pmissingsamples" optional="True" type="select">
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53 <option selected="True" value="None">Selection is Optional</option>
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54 <option value="error">error</option>
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55 <option value="ignore">ignore</option>
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56 </param>
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57 <param label="--p-missing-values: " name="pmissingvalues" optional="True" type="select">
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58 <option selected="True" value="None">Selection is Optional</option>
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59 <option value="drop_samples">drop_samples</option>
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60 <option value="drop_features">drop_features</option>
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61 <option value="error">error</option>
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62 <option value="fill">fill</option>
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63 </param>
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64 <param label="--p-drop-all-unique: --p-drop-all-unique: / --p-no-drop-all-unique If True, columns that contain a unique value for every ID will be dropped. [default: False]" name="pdropallunique" selected="False" type="boolean" />
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65 <param label="--examples: Show usage examples and exit." name="examples" optional="False" type="data" />
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66
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67 </inputs>
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68
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69 <outputs>
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70 <data format="qza" label="${tool.name} on ${on_string}: convertedtable.qza" name="oconvertedtable" />
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71
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72 </outputs>
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73
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74 <help><![CDATA[
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75 Convert (and merge) positive numeric metadata (in)to feature table.
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76 ###############################################################
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77
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78 Convert numeric sample metadata from TSV file into a feature table.
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79 Optionally merge with an existing feature table. Only numeric metadata will
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80 be converted; categorical columns will be silently dropped. By default, if
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81 a table is used as input only samples found in both the table and metadata
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82 (intersection) are merged, and others are silently dropped. Set
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83 missing_samples="error" to raise an error if samples found in the table are
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84 missing from the metadata file. The metadata file can always contain a
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85 superset of samples. Note that columns will be dropped if they are non-
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86 numeric, contain no unique values (zero variance), contain only empty
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87 cells, or contain negative values. This method currently only converts
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88 postive numeric metadata into feature data. Tip: convert categorical
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89 columns to dummy variables to include them in the output feature table.
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90
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91 Parameters
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92 ----------
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93 metadata : Metadata
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94 Metadata file to convert to feature table.
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95 table : FeatureTable[Frequency], optional
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96 Feature table containing all features that should be used for target
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97 prediction.
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98 missing_samples : Str % Choices('error', 'ignore'), optional
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99 How to handle missing samples in metadata. "error" will fail if missing
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100 samples are detected. "ignore" will cause the feature table and
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101 metadata to be filtered, so that only samples found in both files are
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102 retained.
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103 missing_values : Str % Choices('drop_samples', 'drop_features', 'error', 'fill'), optional
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104 How to handle missing values (nans) in metadata. Either "drop_samples"
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105 with missing values, "drop_features" with missing values, "fill"
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106 missing values with zeros, or "error" if any missing values are found.
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107 drop_all_unique : Bool, optional
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108 If True, columns that contain a unique value for every ID will be
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109 dropped.
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110
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111 Returns
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112 -------
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113 converted_table : FeatureTable[Frequency]
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114 Converted feature table
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115 ]]></help>
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116 <macros>
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117 <import>qiime_citation.xml</import>
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118 </macros>
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119 <expand macro="qiime_citation"/>
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120 </tool> |
