<?xml version="1.0" ?>
<tool id="qiime_diversity_adonis" name="qiime diversity adonis" version="2019.4">
	<description> - adonis PERMANOVA test for beta group significance</description>
	<requirements>
		<requirement type="package" version="2019.4">qiime2</requirement>
	</requirements>
	<command><![CDATA[
qiime diversity adonis

--i-distance-matrix=$idistancematrix


#if $input_files_mmetadatafile:
#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 $file_list
#end def
--m-metadata-file=$list_dict_to_string("$input_files_mmetadatafile")
#end if


--p-formula="$pformula"

#if $ppermutations:
 --p-permutations=$ppermutations
#end if

#set $pnjobs = '${GALAXY_SLOTS:-4}'
#if str($pnjobs):
 --p-n-jobs="$pnjobs"
#end if

--o-visualization=ovisualization
;
qiime tools export --input-path ovisualization.qzv --output-path out   && mkdir -p '$ovisualization.files_path'
&& cp -r out/* '$ovisualization.files_path'
&& mv '$ovisualization.files_path/index.html' '$ovisualization'
	]]></command>
	<inputs>
		<param format="qza,no_unzip.zip" label="--i-distance-matrix: ARTIFACT DistanceMatrix     Matrix of distances between pairs of samples. [required]" name="idistancematrix" optional="False" type="data"/>
		<param label="--p-formula: TEXT     Model formula containing only independent terms contained in the sample metadata. These can be continuous variables or factors, and they can have interactions as in a typical R formula. E.g., the formula 'treatment+block' would test whether the input distance matrix partitions based on 'treatment' and 'block' sample metadata. The formula 'treatment*block' would test both of those effects as well as their interaction. Enclose formulae in quotes to avoid unpleasant surprises.                        [required]" name="pformula" optional="False" type="text"/>
		<param label="--p-permutations: INTEGER Range(1, None)     The number of permutations to be run when computing p-values.                                [default: 999]" name="ppermutations" optional="True" min="1" type="integer" value="999"/>

		<repeat name="input_files_mmetadatafile" optional="False" title="--m-metadata-file">
			<param format="tabular" label="--m-metadata-file: Metadata file or artifact viewable as metadata. This option may be supplied multiple times to merge metadata. [required]" name="additional_input" type="data"/>
		</repeat>
	</inputs>
	<outputs>
		<data format="html" label="${tool.name} on ${on_string}: visualization.qzv" name="ovisualization"/>
	</outputs>
	<help><![CDATA[
adonis PERMANOVA test for beta group significance
#################################################

Determine whether groups of samples are significantly different from one
another using the ADONIS permutation-based statistical test in vegan-R. The
function partitions sums of squares of a multivariate data set, and is
directly analogous to MANOVA (multivariate analysis of variance). This
action differs from beta_group_signficance in that it accepts R formulae to
perform multi-way ADONIS tests; beta_group_signficance only performs one-
way tests. For more details see
http://cc.oulu.fi/~jarioksa/softhelp/vegan/html/adonis.html

Parameters
----------
distance_matrix : DistanceMatrix
    Matrix of distances between pairs of samples.
metadata : Metadata
    Sample metadata containing formula terms.
formula : Str
    Model formula containing only independent terms contained in the sample
    metadata. These can be continuous variables or factors, and they can
    have interactions as in a typical R formula. E.g., the formula
    "treatment+block" would test whether the input distance matrix
    partitions based on "treatment" and "block" sample metadata. The
    formula "treatment*block" would test both of those effects as well as
    their interaction. Enclose formulae in quotes to avoid unpleasant
    surprises.
permutations : Int % Range(1, None), optional
    The number of permutations to be run when computing p-values.

Returns
-------
visualization : Visualization
	]]></help>
<macros>
    <import>qiime_citation.xml</import>
</macros>
<expand macro="qiime_citation"/>
</tool>