diff PDAUG_Sequence_Network/PDAUG_Sequence_Network.xml @ 0:e650de82bcc7 draft

"planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
author jay
date Wed, 28 Oct 2020 01:50:00 +0000
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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/PDAUG_Sequence_Network/PDAUG_Sequence_Network.xml	Wed Oct 28 01:50:00 2020 +0000
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+<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>
+
+
+