<tool id="pdaug_sequence_similarity_network" name="PDAUG Sequence Similarity Network" version="0.1.0" python_template_version="3.6">
	<description>Generates a sequence similarity network</description>

    <requirements>
      <requirement type="package" version="0.12.0">python-Levenshtein</requirement>
      <requirement type="package" version="3.2.2">matplotlib</requirement> 
      <requirement type="package" version="2.5">networkx</requirement>
    </requirements>

    <command detect_errors="exit_code"><![CDATA[

        python '$__tool_directory__/PDAUG_Sequence_Network.py' --InFile '$input1'  --OutFile 'out.png'            
    ]]></command>

    <inputs>
      <param name="input1" type="data" format="fasta"  label="Input fasta file" argument= "--InFile" help="Input fasta file with peptides"/>

    </inputs>

    <outputs>   
        <data name='output2' format='png' label="${tool.name} on $on_string - (PNG)" from_work_dir="out.png" />

    </outputs>
 
    <tests>
        <test>
            <param name="input1" value="positive.fasta"/>
            <output name="output2" file="out.png" compare="sim_size" delta="10000" />
        </test>
    </tests>

    <help><![CDATA[
.. class:: infomark

**What it does**

This tool calculates Levenshtein distance between peptide sequences and plots the data in the form of a sequence similarity network.

-----

**Inputs**
    * **--InFile** Takes peptide sequences as fasta file. 

-----

**Outputs**
    * Return html report file.]]></help>
    <citations>
<citation type="bibtex">
  @misc{PDAUGGITHUB, 
    author = {Joshi, Jayadev  and Blankenberg, Daniel}, 
    year = {2020}, 
    title ={PDAUG - a Galaxy based toolset for peptide library analysis, visualization, and machine learning modeling}, 
    publisher = {GitHub}, 
    journal = {GitHub repository}, 
    url =
    {https://github.com/jaidevjoshi83/pdaug.git}, 
    }
</citation>
</citations>
</tool>