--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/id_posterior_error_probability.xml	Fri May 10 17:31:05 2013 -0400
@@ -0,0 +1,45 @@
+<tool id="openms_id_posterior_error_probability" version="0.1.0" name="ID Posterior Error Probability">
+  <description>
+    Tool to estimate the probability of peptide hits to be incorrectly assigned.
+  </description>
+  <macros>
+    <import>macros.xml</import>
+  </macros>
+  <expand macro="stdio" />
+  <expand macro="requires" />
+  <command interpreter="python">
+    openms_wrapper.py --executable 'IDPosteriorErrorProbability' --config $config
+  </command>
+  <configfiles>
+    <configfile name="config">[simple_options]
+in=${input1}
+out=${out}
+split_charge=${split_charge}
+top_hits_only=${top_hits_only}
+</configfile>
+  </configfiles>
+  <inputs>
+    <param format="idxml" name="input1" type="data" label="idXML Input" />
+    <param name="split_charge" type="boolean" label="Split Charge" help="The search engine scores are split by charge if this flag is set. Thus, for each charge state a new model will be computed." checked="false" truevalue="true" falsevalue="false" />
+    <param name="top_hits_only" type="boolean" label="Use Only Top Hits" help="If set only the top hits of every PeptideIdentification will be used" checked="false" truevalue="true" falsevalue="false" />
+    <!-- TODO: Advanced Options -->
+  </inputs>
+  <outputs>
+    <data format="idxml" name="out" />
+  </outputs>
+  <help>
+**What it does**
+
+By default an estimation is performed using the (inverse) Gumbel distribution for incorrectly assigned sequences and a Gaussian distribution for correctly assigned sequences. The probabilities are calculated by using Bayes' law, similar to PeptideProphet. Alternatively, a second Gaussian distribution can be used for incorrectly assigned sequences. At the moment, IDPosteriorErrorProbability is able to handle X!Tandem, Mascot, MyriMatch and OMSSA scores.
+
+No target/decoy information needs to be provided, since the model fits are done on the mixed distribution.
+
+In order to validate the computed probabilities one can adjust the fit_algorithm subsection.
+
+**Citation**
+
+For the underlying tool, please cite ``Marc Sturm, Andreas Bertsch, Clemens Gröpl, Andreas Hildebrandt, Rene Hussong, Eva Lange, Nico Pfeifer, Ole Schulz-Trieglaff, Alexandra Zerck, Knut Reinert, and Oliver Kohlbacher, 2008. OpenMS – an Open-Source Software Framework for Mass Spectrometry. BMC Bioinformatics 9: 163. doi:10.1186/1471-2105-9-163.``
+
+If you use this tool in Galaxy, please cite Chilton J, et al. https://bitbucket.org/galaxyp/galaxyp-toolshed-openms
+  </help>
+</tool>