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comparison qiime2/qiime_gneiss_gradient-clustering.xml @ 0:370e0b6e9826 draft

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author florianbegusch
date Wed, 17 Jul 2019 03:05:17 -0400
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1 <?xml version="1.0" ?>
2 <tool id="qiime_gneiss_gradient-clustering" name="qiime gneiss gradient-clustering" version="2019.4">
3 <description> - Hierarchical clustering using gradient information.</description>
4 <requirements>
5 <requirement type="package" version="2019.4">qiime2</requirement>
6 </requirements>
7 <command><![CDATA[
8 qiime gneiss gradient-clustering
9
10 --i-table=$itable
11 --m-gradient-column="$mgradientcolumn"
12
13
14 #def list_dict_to_string(list_dict):
15 #set $file_list = list_dict[0]['additional_input'].__getattr__('file_name')
16 #for d in list_dict[1:]:
17 #set $file_list = $file_list + ',' + d['additional_input'].__getattr__('file_name')
18 #end for
19 #return $file_list
20 #end def
21
22 --m-gradient-file=$list_dict_to_string($input_files_mgradientfile)
23
24
25 #if $pnoweighted:
26 --p-no-weighted
27 #end if
28
29 --o-clustering=oclustering
30 ;
31 cp oclustering.qza $oclustering
32 ]]></command>
33 <inputs>
34 <param format="qza,no_unzip.zip" label="--i-table: ARTIFACT FeatureTable[Frequency | RelativeFrequency | Composition] The feature table containing the samples in which the columns will be clustered. [required]" name="itable" optional="False" type="data"/>
35 <param label="--m-gradient-column: COLUMN MetadataColumn[Numeric] Contains gradient values to sort the features and samples. [required]" name="mgradientcolumn" optional="False" type="text"/>
36 <param label="--p-no-weighted : Specifies if abundance or presence/absence information should be used to perform the clustering. [default: False]" name="pnoweighted" selected="False" type="boolean"/>
37
38 <repeat name="input_files_mgradientfile" optional="False" title="--m-gradient-file">
39 <param label="--m-gradient-file: Metadata file or artifact viewable as metadata. This option may be supplied multiple times to merge metadata. [required]" name="additional_input" type="data" format="tabular,qza,no_unzip.zip" />
40 </repeat>
41
42 </inputs>
43 <outputs>
44 <data format="qza" label="${tool.name} on ${on_string}: clustering.qza" name="oclustering"/>
45 </outputs>
46 <help><![CDATA[
47 Hierarchical clustering using gradient information.
48 ###################################################
49
50 Build a bifurcating tree that represents a hierarchical clustering of
51 features. The hiearchical clustering uses Ward hierarchical clustering
52 based on the mean difference of gradients that each feature is observed in.
53 This method is primarily used to sort the table to reveal the underlying
54 block-like structures.
55
56 Parameters
57 ----------
58 table : FeatureTable[Frequency | RelativeFrequency | Composition]
59 The feature table containing the samples in which the columns will be
60 clustered.
61 gradient : MetadataColumn[Numeric]
62 Contains gradient values to sort the features and samples.
63 weighted : Bool, optional
64 Specifies if abundance or presence/absence information should be used
65 to perform the clustering.
66
67 Returns
68 -------
69 clustering : Hierarchy
70 A hierarchy of feature identifiers where each tip corresponds to the
71 feature identifiers in the table. This tree can contain tip ids that
72 are not present in the table, but all feature ids in the table must be
73 present in this tree.
74 ]]></help>
75 <macros>
76 <import>qiime_citation.xml</import>
77 </macros>
78 <expand macro="qiime_citation"/>
79 </tool>