diff qiime2-2020.8/qiime_gneiss_gradient-clustering.xml @ 20:d93d8888f0b0 draft

Uploaded

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/qiime2-2020.8/qiime_gneiss_gradient-clustering.xml	Fri Sep 04 12:44:24 2020 +0000
@@ -0,0 +1,108 @@
+<?xml version="1.0" ?>
+<tool id="qiime_gneiss_gradient-clustering" name="qiime gneiss gradient-clustering"
+      version="2020.8">
+  <description>Hierarchical clustering using gradient information.</description>
+  <requirements>
+    <requirement type="package" version="2020.8">qiime2</requirement>
+  </requirements>
+  <command><![CDATA[
+qiime gneiss gradient-clustering
+
+--i-table=$itable
+
+#if str($mgradientfile) != 'None':
+--m-gradient-file=$mgradientfile
+#end if
+
+#if '__ob__' in str($mgradientcolumn):
+  #set $mgradientcolumn_temp = $mgradientcolumn.replace('__ob__', '[')
+  #set $mgradientcolumn = $mgradientcolumn_temp
+#end if
+#if '__cb__' in str($mgradientcolumn):
+  #set $mgradientcolumn_temp = $mgradientcolumn.replace('__cb__', ']')
+  #set $mgradientcolumn = $mgradientcolumn_temp
+#end if
+#if 'X' in str($mgradientcolumn):
+  #set $mgradientcolumn_temp = $mgradientcolumn.replace('X', '\\')
+  #set $mgradientcolumn = $mgradientcolumn_temp
+#end if
+#if '__sq__' in str($mgradientcolumn):
+  #set $mgradientcolumn_temp = $mgradientcolumn.replace('__sq__', "'")
+  #set $mgradientcolumn = $mgradientcolumn_temp
+#end if
+#if '__db__' in str($mgradientcolumn):
+  #set $mgradientcolumn_temp = $mgradientcolumn.replace('__db__', '"')
+  #set $mgradientcolumn = $mgradientcolumn_temp
+#end if
+
+--m-gradient-column=$mgradientcolumn
+
+
+#if $pignoremissingsamples:
+ --p-ignore-missing-samples
+#end if
+
+#if $pnoweighted:
+ --p-no-weighted
+#end if
+
+--o-clustering=oclustering
+
+#if str($examples) != 'None':
+--examples=$examples
+#end if
+
+;
+cp oclustering.qza $oclustering
+
+  ]]></command>
+  <inputs>
+    <param format="qza,no_unzip.zip" label="--i-table: ARTIFACT FeatureTable[Frequency | RelativeFrequency | Composition]       The feature table containing the samples in which the columns will be clustered.                   [required]" name="itable" optional="False" type="data" />
+    <param format="tabular,qza,no_unzip.zip" label="--m-gradient-file: METADATA" name="mgradientfile" optional="False" type="data" />
+    <param label="--m-gradient-column: COLUMN  MetadataColumn[Numeric] Contains gradient values to sort the features and samples.                                     [required]" name="mgradientcolumn" optional="False" type="text" />
+    <param label="--p-ignore-missing-samples: --p-ignore-missing-samples: / --p-no-ignore-missing-samples [default: False]" name="pignoremissingsamples" selected="False" type="boolean" />
+    <param label="--p-no-weighted: Do not specifies if abundance or presence/absence information should be used to perform the clustering. [default: True]" name="pnoweighted" selected="False" type="boolean" />
+    <param label="--examples: Show usage examples and exit." name="examples" optional="False" type="data" />
+    
+  </inputs>
+
+  <outputs>
+    <data format="qza" label="${tool.name} on ${on_string}: clustering.qza" name="oclustering" />
+    
+  </outputs>
+
+  <help><![CDATA[
+Hierarchical clustering using 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[Frequency | RelativeFrequency | Composition]
+    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.
+ignore_missing_samples : Bool, optional
+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 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>
\ No newline at end of file