view qiime2-2020.8/qiime_gneiss_correlation-clustering.xml @ 21:a98d7ab297f1 draft

Deleted selected files
author florianbegusch
date Fri, 04 Sep 2020 12:46:48 +0000
parents d93d8888f0b0
children
line wrap: on
line source

<?xml version="1.0" ?>
<tool id="qiime_gneiss_correlation-clustering" name="qiime gneiss correlation-clustering"
      version="2020.8">
  <description>Hierarchical clustering using feature correlation.</description>
  <requirements>
    <requirement type="package" version="2020.8">qiime2</requirement>
  </requirements>
  <command><![CDATA[
qiime gneiss correlation-clustering

--i-table=$itable

--p-pseudocount=$ppseudocount

--o-clustering=oclustering

#if str($examples) != 'None':
--examples=$examples
#end if

;
cp oclustering.qza $oclustering

  ]]></command>
  <inputs>
    <param format="qza,no_unzip.zip" label="--i-table: ARTIFACT FeatureTable[Frequency] The feature table containing the samples in which the columns will be clustered.            [required]" name="itable" optional="False" type="data" />
    <param label="--p-pseudocount: NUMBER  The value to add to zero counts in the feature table.                                [default: 0.5]" name="ppseudocount" optional="True" type="float" value="0.5" />
    <param label="--examples: Show usage examples and exit." name="examples" optional="False" type="data" />
    
  </inputs>

  <outputs>
    <data format="qza" label="${tool.name} on ${on_string}: clustering.qza" name="oclustering" />
    
  </outputs>

  <help><![CDATA[
Hierarchical clustering using feature correlation.
###############################################################

Build a bifurcating tree that represents a hierarchical clustering of
features.  The hiearchical clustering uses Ward hierarchical clustering
based on the degree of proportionality between features.

Parameters
----------
table : FeatureTable[Frequency]
    The feature table containing the samples in which the columns will be
    clustered.
pseudocount : Float, optional
    The value to add to zero counts in the feature table.

Returns
-------
clustering : Hierarchy
    A hierarchy of feature identifiers where each tip corresponds 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>
  <macros>
    <import>qiime_citation.xml</import>
  </macros>
  <expand macro="qiime_citation"/>
</tool>