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comparison qiime2/qiime_sample-classifier_metatable.xml @ 0:370e0b6e9826 draft

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author florianbegusch
date Wed, 17 Jul 2019 03:05:17 -0400
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-1:000000000000 0:370e0b6e9826
1 <?xml version="1.0" ?>
2 <tool id="qiime_sample-classifier_metatable" name="qiime sample-classifier metatable" version="2019.4">
3 <description> - Convert (and merge) positive numeric metadata (in)to feature table.</description>
4 <requirements>
5 <requirement type="package" version="2019.4">qiime2</requirement>
6 </requirements>
7 <command><![CDATA[
8 qiime sample-classifier metatable
9
10
11 #if str($itable) != 'None':
12 --i-table=$itable
13 #end if
14
15 #if str($pmissingsamples) != 'None':
16 --p-missing-samples=$pmissingsamples
17 #end if
18
19 #if str($pmissingvalues) != 'None':
20 --p-missing-values=$pmissingvalues
21 #end if
22
23
24 #if $input_files_mmetadatafile:
25 #def list_dict_to_string(list_dict):
26 #set $file_list = list_dict[0]['additional_input'].__getattr__('file_name')
27 #for d in list_dict[1:]:
28 #set $file_list = $file_list + ' --m-metadata-file=' + d['additional_input'].__getattr__('file_name')
29 #end for
30 #return $file_list
31 #end def
32 --m-metadata-file=$list_dict_to_string($input_files_mmetadatafile)
33 #end if
34
35
36 --o-converted-table=oconvertedtable
37 ;
38 cp oconvertedtable.qza $oconvertedtable
39 ]]></command>
40 <inputs>
41 <param format="qza,no_unzip.zip" label="--i-table: ARTIFACT FeatureTable[Frequency] Feature table containing all features that should be used for target prediction. [optional]" name="itable" optional="True" type="data"/>
42 <param label="--p-missing-samples: " name="pmissingsamples" optional="True" type="select">
43 <option selected="True" value="None">Selection is Optional</option>
44 <option value="error">error</option>
45 <option value="ignore">ignore</option>
46 </param>
47 <param label="--p-missing-values: " name="pmissingvalues" optional="True" type="select">
48 <option selected="True" value="None">Selection is Optional</option>
49 <option value="drop_samples">drop_samples</option>
50 <option value="drop_features">drop_features</option>
51 <option value="error">error</option>
52 <option value="fill">fill</option>
53 </param>
54
55 <repeat name="input_files_mmetadatafile" optional="True" title="--m-metadata-file">
56 <param label="--m-metadata-file: Metadata file or artifact viewable as metadata. This option may be supplied multiple times to merge metadata. [optional]" name="additional_input" type="data" format="tabular,qza,no_unzip.zip" />
57 </repeat>
58
59 </inputs>
60 <outputs>
61 <data format="qza" label="${tool.name} on ${on_string}: convertedtable.qza" name="oconvertedtable"/>
62 </outputs>
63 <help><![CDATA[
64 Convert (and merge) positive numeric metadata (in)to feature table.
65 ###################################################################
66
67 Convert numeric sample metadata from TSV file into a feature table.
68 Optionally merge with an existing feature table. Only numeric metadata will
69 be converted; categorical columns will be silently dropped. By default, if
70 a table is used as input only samples found in both the table and metadata
71 (intersection) are merged, and others are silently dropped. Set
72 missing_samples="error" to raise an error if samples found in the table are
73 missing from the metadata file. The metadata file can always contain a
74 superset of samples. Note that columns will be dropped if they are non-
75 numeric, contain only unique values, contain no unique values (zero
76 variance), contain only empty cells, or contain negative values. This
77 method currently only converts postive numeric metadata into feature data.
78 Tip: convert categorical columns to dummy variables to include them in the
79 output feature table.
80
81 Parameters
82 ----------
83 metadata : Metadata
84 Metadata file to convert to feature table.
85 table : FeatureTable[Frequency], optional
86 Feature table containing all features that should be used for target
87 prediction.
88 missing_samples : Str % Choices('error', 'ignore'), optional
89 How to handle missing samples in metadata. "error" will fail if missing
90 samples are detected. "ignore" will cause the feature table and
91 metadata to be filtered, so that only samples found in both files are
92 retained.
93 missing_values : Str % Choices('drop_samples', 'drop_features', 'error', 'fill'), optional
94 How to handle missing values (nans) in metadata. Either "drop_samples"
95 with missing values, "drop_features" with missing values, "fill"
96 missing values with zeros, or "error" if any missing values are found.
97
98 Returns
99 -------
100 converted_table : FeatureTable[Frequency]
101 Converted feature table
102 ]]></help>
103 <macros>
104 <import>qiime_citation.xml</import>
105 </macros>
106 <expand macro="qiime_citation"/>
107 </tool>