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view qiime_gneiss_gradient-clustering.xml @ 0:09b7bcb72fa7 draft
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author | florianbegusch |
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date | Thu, 24 May 2018 02:11:44 -0400 |
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<?xml version="1.0" ?> <tool id="qiime_gneiss_gradient-clustering" name="qiime gneiss gradient-clustering" version="2018.4"> <description> - Hierarchical clustering using gradient information.</description> <requirements> <requirement type="package" version="2018.4">qiime2</requirement> </requirements> <command> <![CDATA[ qiime gneiss gradient-clustering --i-table=$itable --m-gradient-column="$mgradientcolumn" #def list_dict_to_string(list_dict): #set $file_list = list_dict[0]['additional_input'].__getattr__('file_name') #for d in list_dict[1:]: #set $file_list = $file_list + ',' + d['additional_input'].__getattr__('file_name') #end for #return $file_list #end def --m-gradient-file=$list_dict_to_string($input_files_mgradientfile) #if str($cmdconfig) != 'None': --cmd-config=$cmdconfig #end if #if $pweighted: --p-weighted #else --p-no-weighted #end if --o-clustering=oclustering; cp oclustering.qza $oclustering; ]]> </command> <inputs> <param format="qza,no_unzip.zip" label="--i-table: FeatureTable[Composition | Frequency | RelativeFrequency] The feature table containing the samples in which the columns will be clustered. [required]" name="itable" optional="False" type="data"/> <param label="--m-gradient-column: MetadataColumn[Numeric] Column from metadata file or artifact viewable as metadata. Contains gradient values to sort the features and samples. [required]" name="mgradientcolumn" optional="False" type="text"/> <repeat name="input_files_mgradientfile" optional="False" title="--m-gradient-file"> <param label="--m-gradient-file: Metadata file or artifact viewable as metadata. This option may be supplied multiple times to merge metadata. [required]" name="additional_input" type="data" format="tabular,qza,no_unzip.zip" /> </repeat> <param label="--p-weighted: --p-no-weighted Specifies if abundance or presence/absence information should be used to perform the clustering. [default: True]" name="pweighted" checked="True" type="boolean"/> <param label="--cmd-config: Use config file for command options" name="cmdconfig" optional="True" type="data"/> </inputs> <outputs> <data format="qza" label="${tool.name} on ${on_string}: clustering.qza" name="oclustering"/> </outputs> <help> <![CDATA[ Hierarchical clustering using gradient information. ---------------------------------------------------- Build a bifurcating tree that represents a hierarchical clustering of features. The hiearchical clustering uses Ward hierarchical clustering based on the mean difference of gradients that each feature is observed in. This method is primarily used to sort the table to reveal the underlying block-like structures. Parameters ---------- table : FeatureTable[Composition | Frequency | RelativeFrequency] The feature table containing the samples in which the columns will be clustered. gradient : MetadataColumn[Numeric] Contains gradient values to sort the features and samples. weighted : Bool, optional Specifies if abundance or presence/absence information should be used to perform the clustering. Returns ------- clustering : Hierarchy A hierarchy of feature identifiers where each tipcorresponds to the feature identifiers in the table. This tree can contain tip ids that are not present in the table, but all feature ids in the table must be present in this tree. ]]> </help> </tool>