<tool id="mothur_dist_shared" name="Dist.shared" version="1.23.0" force_history_refresh="True">
 <description>Generate a phylip-formatted dissimilarity distance matrix among multiple groups</description>
 <command interpreter="python">
  mothur_wrapper.py 
  --cmd='dist.shared'
  --result='^mothur.\S+\.logfile$:'$logfile
  --outputdir='$logfile.extra_files_path'
  #if $as_datasets.__str__ == "yes":
   --datasetid='$logfile.id' --new_file_path='$__new_file_path__'
   #if len($output.__str__) > 0:
    #if $output.__str__ == 'square':
     --new_datasets='^\S+?\.([a-z]+\.(unique|[0-9.]*)\.(square|lt))\.dist$:square.dist'
    #elif $output.__str__ == 'lt':
     --new_datasets='^\S+?\.([a-z]+\.(unique|[0-9.]*)\.(square|lt))\.dist$:lower.dist'
    #end if
   #else:
    --new_datasets='^\S+?\.([a-z]+\.(unique|[0-9.]*)\.(square|lt))\.dist$:lower.dist'
   #end if
  #end if
  --shared=$otu
  #if $label.__str__ != "None" and len($label.__str__) > 0:
   --label='$label'
  #end if
  #if $groups.__str__ != "None" and len($groups.__str__) > 0:
   --groups=$groups
  #end if
  #if $calc.__str__ != "None" and len($calc.__str__) > 0:
   --calc=$calc
  #end if
  #if $output.__str__ != "None" and len($output.__str__) > 0:
   --output=$output
  #end if
  --processors=8
 </command>
 <inputs>
  <!-- list,group  or shared -->
  <param name="otu" type="data" format="shared" label="shared - OTU Shared"/>
  <param name="label" type="select" label="label - OTU Labels to calculate" multiple="true">
   <options from_dataset="otu">
    <column name="name" index="0"/>
    <column name="value" index="0"/>
    <filter type="static_value" name="ignore_header" keep="False" column="0" value = "label"/>
    <filter type="unique_value" name="unq_lbl" column="0" />
   </options>
  </param>
  <param name="groups" type="select" label="groups - Groups to analyze" multiple="true">
   <options from_dataset="otu">
    <column name="name" index="1"/>
    <column name="value" index="1"/>
    <filter type="static_value" name="ignore_header" keep="False" column="1" value = "Group"/>
    <filter type="unique_value" name="unq_grp" column="1" />
   </options>
  </param>
  <param name="calc" type="select" label="calc - Calculators (Uses defaults if none selected)" multiple="true">
   <option value="sharedsobs">sharedsobs - Shared community richness the observed richness shared between two or more samples</option>
   <option value="sharedchao">sharedchao - Shared community richness the two or more sample shared Chao1 richness estimator</option>
   <option value="sharedace">sharedace - Shared community richness the two sample shared ACE richness estimator</option>
   <option value="anderberg">anderberg - Community Membership Similarity the Anderberg similarity coefficient</option>
   <option value="jclass" selected="true">jclass - Community Membership Similarity the traditional Jaccard similarity coefficient based on the observed richness</option>
   <option value="jest">jest - Community Membership Similarity the Jaccard similarity coefficient based on the Chao1 estimated richnesses</option>
   <option value="kulczynski">kulczynski - Community Membership Similarity the Kulczynski similarity coefficient</option>
   <option value="kulczynskicody">kulczynskicody - Community Membership Similarity the Kulczynski-Cody similarity coefficient</option>
   <option value="kstest">kstest - Community Membership Similarity Kolmogorov-Smirnov test</option>
   <option value="lennon">lennon - Community Membership Similarity the Lennon similarity coefficient</option>
   <option value="ochiai">ochiai - Community Membership Similarity the Ochiai similarity coefficient</option>
   <option value="sorclass">sorclass - Community Membership Similarity the Sorenson similarity coefficient based on the observed richness</option>
   <option value="sorest">sorest - Community Membership Similarity the Sorenson similarity coefficient based on the Chao1 estimated richnesses</option>
   <option value="whittaker">whittaker - Community Membership Similarity the Whittaker similarity coefficient</option>
   <option value="hamming">hamming - Community Membership Similarity -</option>
   <option value="memchi2">memchi2 - Community Membership Similarity -</option>
   <option value="memchord">memchord - Community Membership Similarity -</option>
   <option value="memeuclidean">memeuclidean - Community Membership Similarity -</option>
   <option value="mempearson">mempearson - Community Membership Similarity -</option>
   <option value="braycurtis">braycurtis - Community Structure Similarity the Bray-Curtis similarity coefficient</option>
   <option value="jabund">jabund - Community Structure Similarity the abundance-based Jaccard similarity coefficient</option>
   <option value="morisitahorn">morisitahorn - Community Structure Similarity the Morisita-Horn similarity coefficient</option>
   <option value="sorabund">sorabund - Community Structure Similarity the abundance-based Sorenson similarity coefficient</option>
   <option value="thetan">thetan - Community Structure Similarity the Smith theta similarity coefficient</option>
   <option value="thetayc" selected="true">thetayc - Community Structure Similarity the Yue &amp; Clayton theta similarity coefficient</option>
   <option value="canberra">canberra - Community Structure Similarity -</option>
   <option value="gower">gower - Community Structure Similarity -</option>
   <option value="hellinger">hellinger - Community Structure Similarity -</option>
   <option value="manhattan">manhattan - Community Structure Similarity -</option>
   <option value="odum">odum - Community Structure Similarity -</option>
   <option value="soergel">soergel - Community Structure Similarity -</option>
   <option value="spearman">spearman - Community Structure Similarity -</option>
   <option value="speciesprofile">speciesprofile - Community Structure Similarity -</option>
   <option value="structchi2">structchi2 - Community Structure Similarity -</option>
   <option value="structchord">structchord - Community Structure Similarity -</option>
   <option value="structeuclidean">structeuclidean - Community Structure Similarity -</option>
   <option value="structkulczynski">structkulczynski - Community Structure Similarity -</option>
   <option value="structpearson">structpearson - Community Structure Similarity -</option>
   <option value="sharednseqs">sharednseqs - Utility the number of sequences in two samples</option>
   <option value="sharedobserved">sharedobserved - Utility the number of sequences in two samples</option>
  </param>
  <param name="output" type="select" label="output - Distance Matrix Output Format" help="A Distance Matrix will be generated for each calculator label pair">
   <option value="lt">Phylip formatted Lower Triangle Matrix</option>
   <option value="square">Phylip formatted Square Matrix</option>
  </param>
  <param name="as_datasets" type="boolean" truevalue="yes" falsevalue="no" checked="true" label="Create a new history dataset for each distance matrix"/>
 </inputs>
 <outputs>
  <data format="html" name="logfile" label="${tool.name} on ${on_string}: logfile" />
 </outputs>
 <requirements>
  <requirement type="binary">mothur</requirement>
 </requirements>
 <tests>
 </tests>
 <help>
**Mothur Overview**

Mothur_, initiated by Dr. Patrick Schloss and his software development team
in the Department of Microbiology and Immunology at The University of Michigan,
provides bioinformatics for the microbial ecology community.

.. _Mothur: http://www.mothur.org/wiki/Main_Page

**Command Documenation**

The dist.shared_ command will generate a phylip-formatted_distance_matrix_ that describes the dissimilarity (1-similarity) among multiple groups from a shared_ file. For calc parameter choices see: http://www.mothur.org/wiki/Calculators

.. _phylip-formatted_distance_matrix: http://www.mothur.org/wiki/Phylip-formatted_distance_matrix
.. _shared: http://www.mothur.org/wiki/Shared_file
.. _dist.shared: http://www.mothur.org/wiki/Dist.shared


 </help>
</tool>