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comparison qiime2-2020.8/qiime_sample-classifier_metatable.xml @ 20:d93d8888f0b0 draft

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author florianbegusch
date Fri, 04 Sep 2020 12:44:24 +0000
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19:6c48f8d82424 20:d93d8888f0b0
1 <?xml version="1.0" ?>
2 <tool id="qiime_sample-classifier_metatable" name="qiime sample-classifier metatable"
3 version="2020.8">
4 <description>Convert (and merge) positive numeric metadata (in)to feature table.</description>
5 <requirements>
6 <requirement type="package" version="2020.8">qiime2</requirement>
7 </requirements>
8 <command><![CDATA[
9 qiime sample-classifier metatable
10
11 #if str($itable) != 'None':
12 --i-table=$itable
13 #end if
14 # if $input_files_mmetadatafile:
15 # def list_dict_to_string(list_dict):
16 # set $file_list = list_dict[0]['additional_input'].__getattr__('file_name')
17 # for d in list_dict[1:]:
18 # set $file_list = $file_list + ' --m-metadata-file=' + d['additional_input'].__getattr__('file_name')
19 # end for
20 # return $file_list
21 # end def
22 --m-metadata-file=$list_dict_to_string($input_files_mmetadatafile)
23 # end if
24
25 #if str($pmissingsamples) != 'None':
26 --p-missing-samples=$pmissingsamples
27 #end if
28
29 #if str($pmissingvalues) != 'None':
30 --p-missing-values=$pmissingvalues
31 #end if
32
33 #if $pdropallunique:
34 --p-drop-all-unique
35 #end if
36
37 --o-converted-table=oconvertedtable
38
39 #if str($examples) != 'None':
40 --examples=$examples
41 #end if
42
43 ;
44 cp oconvertedtable.qza $oconvertedtable
45
46 ]]></command>
47 <inputs>
48 <param format="qza,no_unzip.zip" label="--i-table: ARTIFACT FeatureTable[Frequency] Feature table containing all features that should be used for target prediction. [optional]" name="itable" optional="False" type="data" />
49 <repeat name="input_files_mmetadatafile" optional="False" title="--m-metadata-file">
50 <param format="tabular,qza,no_unzip.zip" label="--m-metadata-file: METADATA... (multiple Metadata file to convert to feature table. arguments will be merged) [required]" name="additional_input" optional="False" type="data" />
51 </repeat>
52 <param label="--p-missing-samples: " name="pmissingsamples" optional="True" type="select">
53 <option selected="True" value="None">Selection is Optional</option>
54 <option value="error">error</option>
55 <option value="ignore">ignore</option>
56 </param>
57 <param label="--p-missing-values: " name="pmissingvalues" optional="True" type="select">
58 <option selected="True" value="None">Selection is Optional</option>
59 <option value="drop_samples">drop_samples</option>
60 <option value="drop_features">drop_features</option>
61 <option value="error">error</option>
62 <option value="fill">fill</option>
63 </param>
64 <param label="--p-drop-all-unique: --p-drop-all-unique: / --p-no-drop-all-unique If True, columns that contain a unique value for every ID will be dropped. [default: False]" name="pdropallunique" selected="False" type="boolean" />
65 <param label="--examples: Show usage examples and exit." name="examples" optional="False" type="data" />
66
67 </inputs>
68
69 <outputs>
70 <data format="qza" label="${tool.name} on ${on_string}: convertedtable.qza" name="oconvertedtable" />
71
72 </outputs>
73
74 <help><![CDATA[
75 Convert (and merge) positive numeric metadata (in)to feature table.
76 ###############################################################
77
78 Convert numeric sample metadata from TSV file into a feature table.
79 Optionally merge with an existing feature table. Only numeric metadata will
80 be converted; categorical columns will be silently dropped. By default, if
81 a table is used as input only samples found in both the table and metadata
82 (intersection) are merged, and others are silently dropped. Set
83 missing_samples="error" to raise an error if samples found in the table are
84 missing from the metadata file. The metadata file can always contain a
85 superset of samples. Note that columns will be dropped if they are non-
86 numeric, contain no unique values (zero variance), contain only empty
87 cells, or contain negative values. This method currently only converts
88 postive numeric metadata into feature data. Tip: convert categorical
89 columns to dummy variables to include them in the output feature table.
90
91 Parameters
92 ----------
93 metadata : Metadata
94 Metadata file to convert to feature table.
95 table : FeatureTable[Frequency], optional
96 Feature table containing all features that should be used for target
97 prediction.
98 missing_samples : Str % Choices('error', 'ignore'), optional
99 How to handle missing samples in metadata. "error" will fail if missing
100 samples are detected. "ignore" will cause the feature table and
101 metadata to be filtered, so that only samples found in both files are
102 retained.
103 missing_values : Str % Choices('drop_samples', 'drop_features', 'error', 'fill'), optional
104 How to handle missing values (nans) in metadata. Either "drop_samples"
105 with missing values, "drop_features" with missing values, "fill"
106 missing values with zeros, or "error" if any missing values are found.
107 drop_all_unique : Bool, optional
108 If True, columns that contain a unique value for every ID will be
109 dropped.
110
111 Returns
112 -------
113 converted_table : FeatureTable[Frequency]
114 Converted feature table
115 ]]></help>
116 <macros>
117 <import>qiime_citation.xml</import>
118 </macros>
119 <expand macro="qiime_citation"/>
120 </tool>