<tool id="qiime_upgma_cluster" name="upgma cluster" version="1.9.1galaxy1">
    <description>Build a UPGMA tree comparing samples</description>
    
    <macros>
        <import>macros.xml</import>
    </macros>

    <expand macro="requirements" />

    <command>
<![CDATA[
        upgma_cluster.py 
            -i upgma_cluster_input 
            -o upgma_cluster_output
]]>            
    </command>

    <inputs>
        <param label="-i/--input_path: input path.  directory for batch processing, 
            filename for single file operation" name="input_path" type="data"/>
    </inputs>

    <outputs>
        <data format="newick" name="output_tree"/>
    </outputs>

    <tests>
        <test>
        </test>
    </tests>

    <help><![CDATA[
**What it does?**

In addition to using PCoA, it can be useful to cluster samples using UPGMA (Unweighted Pair Group Method with Arithmetic mean, also known as average linkage). As with PCoA, the input to this step is a distance matrix (i.e. resulting file from beta_diversity.py).
The output is a newick formatted tree compatible with most standard tree viewing programs. Batch processing is also available, allowing the analysis of an entire directory of distance matrices.
    ]]>
    </help>

    <citations>
        <expand macro="citations" />
    </citations>
</tool>