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1 <tool id="openms_id_posterior_error_probability" version="0.1.0" name="ID Posterior Error Probability">
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2 <description>
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3 Tool to estimate the probability of peptide hits to be incorrectly assigned.
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4 </description>
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5 <macros>
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6 <import>macros.xml</import>
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7 </macros>
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8 <expand macro="stdio" />
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9 <expand macro="requires" />
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10 <command interpreter="python">
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11 openms_wrapper.py --executable 'IDPosteriorErrorProbability' --config $config
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12 </command>
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13 <configfiles>
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14 <configfile name="config">[simple_options]
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15 in=${input1}
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16 out=${out}
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17 split_charge=${split_charge}
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18 top_hits_only=${top_hits_only}
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19 </configfile>
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20 </configfiles>
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21 <inputs>
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22 <param format="idxml" name="input1" type="data" label="idXML Input" />
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23 <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" />
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24 <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" />
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25 <!-- TODO: Advanced Options -->
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26 </inputs>
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27 <outputs>
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28 <data format="idxml" name="out" />
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29 </outputs>
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30 <help>
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31 **What it does**
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32
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33 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.
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34
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35 No target/decoy information needs to be provided, since the model fits are done on the mixed distribution.
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36
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37 In order to validate the computed probabilities one can adjust the fit_algorithm subsection.
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38
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39 **Citation**
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40
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41 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.``
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42
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43 If you use this tool in Galaxy, please cite Chilton J, et al. https://bitbucket.org/galaxyp/galaxyp-toolshed-openms
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44 </help>
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45 </tool>
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