<tool id="principal_coordinates" name="principal_coordinates" version="1.2.0">
 <description>Principal Coordinates Analysis (PCoA)</description>
 <requirements>
  <requirement type="binary">principal_coordinates.py</requirement>
 </requirements>
 <command interpreter="python">
  qiime_wrapper.py
  principal_coordinates.py
  --input_path=$input_path
  --output_path=$output_path
 </command>
 <inputs>
 <conditional name="run_type">
  <param name="input_type" type="select" label="Input Type" help="Select the type/number of input file(s). If you want to process multiple diversity metrics, select 'multiple files.'">
   <option value="single">Single File</option>
   <option value="multi">Multiple Files</option>
  </param>
  <when value="single">
   <param name="input_path" type="data" format="qiimedistmat"  label="input_path"
   help="path to the input distance matrix file (i.e., the output from beta_diversity.py). [REQUIRED]"/>
  </when>
  <when value="multi">
    <param name="input_path" type="data" format="qiimedistmat"  label="input_path"
   help="Path to the first distance matrix file of the metrics run. Example: if you ran beta diversity for both 1: unweighted and 2: weighted unifrac, choose the unweighted file. [REQUIRED]"/>
  </when>
  </conditional>
 </inputs>
 <outputs>
  <data format="qiimepca" name="output_path" label="${tool.name} on ${on_string}: coordinates"/>
 </outputs>
 <tests>
 </tests>
 <help>For more information, see principle_coordinates_ in the Qiime documentation.
 
Updated and validated 01/18/12 by Amanda Zuzolo, Microbiome Analysis Center, George Mason University, Fairfax, VA
Qiime integration courtesy Jim Johnson, Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN
 
 .. _principle_coordinates: http://qiime.org/scripts/principal_coordinates.html</help>
</tool>