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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="2019.7">
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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="2019.7">qiime2</requirement>
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6 </requirements>
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7 <command><![CDATA[
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8 qiime gneiss gradient-clustering
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9
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10 --i-table=$itable
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11 --m-gradient-column="$mgradientcolumn"
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12
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13
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14 #if $mgradientfile:
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15 --m-gradient-file=$mgradientfile
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16 #end if
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17
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18 #if $pnoweighted:
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19 --p-no-weighted
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20 #end if
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21
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22 --o-clustering=oclustering
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23 ;
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24 cp oclustering.qza $oclustering
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25 ]]></command>
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26 <inputs>
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27 <param format="qza,no_unzip.zip" label="--i-table: ARTIFACT FeatureTable[Frequency | RelativeFrequency | Composition] The feature table containing the samples in which the columns will be clustered. [required]" name="itable" optional="False" type="data"/>
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28 <param label="--m-gradient-column: COLUMN MetadataColumn[Numeric] Contains gradient values to sort the features and samples. [required]" name="mgradientcolumn" optional="False" type="text"/>
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29 <param label="--p-no-weighted : Specifies if abundance or presence/absence information should be used to perform the clustering. [default: False]" name="pnoweighted" selected="False" type="boolean"/>
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30
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31 <param label="--m-gradient-file: " name="mgradientfile" optional="True" type="data" format="tabular,qza,no_unzip.zip" />
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32
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33 </inputs>
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34 <outputs>
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35 <data format="qza" label="${tool.name} on ${on_string}: clustering.qza" name="oclustering"/>
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36 </outputs>
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37 <help><![CDATA[
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38 Hierarchical clustering using gradient information.
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39 ###################################################
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40
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41 Build a bifurcating tree that represents a hierarchical clustering of
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42 features. The hiearchical clustering uses Ward hierarchical clustering
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43 based on the mean difference of gradients that each feature is observed in.
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44 This method is primarily used to sort the table to reveal the underlying
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45 block-like structures.
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46
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47 Parameters
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48 ----------
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49 table : FeatureTable[Frequency | RelativeFrequency | Composition]
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50 The feature table containing the samples in which the columns will be
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51 clustered.
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52 gradient : MetadataColumn[Numeric]
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53 Contains gradient values to sort the features and samples.
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54 weighted : Bool, optional
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55 Specifies if abundance or presence/absence information should be used
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56 to perform the clustering.
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57
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58 Returns
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59 -------
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60 clustering : Hierarchy
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61 A hierarchy of feature identifiers where each tip corresponds to the
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62 feature identifiers in the table. This tree can contain tip ids that
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63 are not present in the table, but all feature ids in the table must be
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64 present in this tree.
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65 ]]></help>
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66 <macros>
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67 <import>qiime_citation.xml</import>
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68 </macros>
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69 <expand macro="qiime_citation"/>
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70 </tool>
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