--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/PTPredict.xml	Wed Mar 01 12:19:47 2017 -0500
@@ -0,0 +1,48 @@
+<?xml version='1.0' encoding='UTF-8'?>
+<!--This is a configuration file for the integration of a tools into Galaxy (https://galaxyproject.org/). This file was automatically generated using CTD2Galaxy.-->
+<!--Proposed Tool Section: [Peptide property prediction]-->
+<tool id="PTPredict" name="PTPredict" version="2.1.0">
+  <description>predicts the likelihood of peptides to be proteotypic via svm_model which is trained by PTModel</description>
+  <macros>
+    <token name="@EXECUTABLE@">PTPredict</token>
+    <import>macros.xml</import>
+  </macros>
+  <expand macro="references"/>
+  <expand macro="stdio"/>
+  <expand macro="requirements"/>
+  <command>PTPredict
+
+#if $param_in:
+  -in $param_in
+#end if
+#if $param_out:
+  -out $param_out
+#end if
+#if $param_svm_model:
+  -svm_model $param_svm_model
+#end if
+#if $param_max_number_of_peptides:
+  -max_number_of_peptides $param_max_number_of_peptides
+#end if
+#if $adv_opts.adv_opts_selector=='advanced':
+    #if $adv_opts.param_force:
+  -force
+#end if
+#end if
+</command>
+  <inputs>
+    <param name="param_in" type="data" format="idxml" optional="False" label="input file" help="(-in) "/>
+    <param name="param_svm_model" type="data" format="txt" optional="False" label="svm model in libsvm format (can be produced by PTModel)" help="(-svm_model) "/>
+    <param name="param_max_number_of_peptides" type="integer" value="100000" label="the maximum number of peptides considered at once (bigger number will lead to faster results but needs more memory)" help="(-max_number_of_peptides) &lt;br&gt;"/>
+    <expand macro="advanced_options">
+      <param name="param_force" display="radio" type="boolean" truevalue="-force" falsevalue="" checked="false" optional="True" label="Overwrite tool specific checks" help="(-force) "/>
+    </expand>
+  </inputs>
+  <outputs>
+    <data name="param_out" format="idxml"/>
+  </outputs>
+  <help>predicts the likelihood of peptides to be proteotypic via svm_model which is trained by PTModel
+
+
+For more information, visit http://ftp.mi.fu-berlin.de/OpenMS/release-documentation/html/TOPP_PTPredict.html</help>
+</tool>