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1 <?xml version="1.0" ?>
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2 <tool id="qiime_gneiss_gradient-clustering" name="qiime gneiss gradient-clustering" version="2018.4">
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3 <description> - Hierarchical clustering using gradient information.</description>
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4 <requirements>
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5 <requirement type="package" version="2018.4">qiime2</requirement>
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6 </requirements>
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7 <command>
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8 <![CDATA[
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9 qiime gneiss gradient-clustering --i-table=$itable --m-gradient-column="$mgradientcolumn"
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10
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11 #def list_dict_to_string(list_dict):
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12 #set $file_list = list_dict[0]['additional_input'].__getattr__('file_name')
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13 #for d in list_dict[1:]:
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14 #set $file_list = $file_list + ',' + d['additional_input'].__getattr__('file_name')
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15 #end for
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16 #return $file_list
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17 #end def
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18
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19 --m-gradient-file=$list_dict_to_string($input_files_mgradientfile)
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20 #if str($cmdconfig) != 'None':
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21 --cmd-config=$cmdconfig
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22 #end if
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23
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24 #if $pweighted:
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25 --p-weighted
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26 #else
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27 --p-no-weighted
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28 #end if
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29
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30 --o-clustering=oclustering;
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31 cp oclustering.qza $oclustering;
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32 ]]>
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33 </command>
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34 <inputs>
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35 <param format="qza,no_unzip.zip" label="--i-table: FeatureTable[Composition | Frequency | RelativeFrequency] The feature table containing the samples in which the columns will be clustered. [required]" name="itable" optional="False" type="data"/>
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36 <param label="--m-gradient-column: MetadataColumn[Numeric] Column from metadata file or artifact viewable as metadata. Contains gradient values to sort the features and samples. [required]" name="mgradientcolumn" optional="False" type="text"/>
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37
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38 <repeat name="input_files_mgradientfile" optional="False" title="--m-gradient-file">
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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" />
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40 </repeat>
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41
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42 <param label="--p-weighted: --p-no-weighted Specifies if abundance or presence/absence information should be used to perform the clustering. [default: True]" name="pweighted" checked="True" type="boolean"/>
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43 <param label="--cmd-config: Use config file for command options" name="cmdconfig" optional="True" type="data"/>
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44 </inputs>
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45 <outputs>
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46 <data format="qza" label="${tool.name} on ${on_string}: clustering.qza" name="oclustering"/>
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47 </outputs>
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48 <help>
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49 <![CDATA[
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50 Hierarchical clustering using gradient information.
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51 ----------------------------------------------------
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52
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53 Build a bifurcating tree that represents a hierarchical clustering of
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54 features. The hiearchical clustering uses Ward hierarchical clustering
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55 based on the mean difference of gradients that each feature is observed in.
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56 This method is primarily used to sort the table to reveal the underlying
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57 block-like structures.
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58
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59 Parameters
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60 ----------
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61 table : FeatureTable[Composition | Frequency | RelativeFrequency]
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62 The feature table containing the samples in which the columns will be
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63 clustered.
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64 gradient : MetadataColumn[Numeric]
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65 Contains gradient values to sort the features and samples.
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66 weighted : Bool, optional
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67 Specifies if abundance or presence/absence information should be used
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68 to perform the clustering.
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69
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70 Returns
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71 -------
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72 clustering : Hierarchy
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73 A hierarchy of feature identifiers where each tipcorresponds to the
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74 feature identifiers in the table. This tree can contain tip ids that
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75 are not present in the table, but all feature ids in the table must be
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76 present in this tree.
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77 ]]>
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78 </help>
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79 </tool>
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