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<?xml version='1.0' encoding='UTF-8'?>
<tool id="IDPosteriorErrorProbability" name="IDPosteriorErrorProbability" version="1.12.0">
  <description>Estimates probabilities for incorrectly assigned peptide sequences and a set of search engine scores using a mixture model.</description>
  <macros>
    <token name="@EXECUTABLE@">IDPosteriorErrorProbability</token>
    <import>macros.xml</import>
  </macros>
  <expand macro="stdio"/>
  <expand macro="requirements"/>
  <command>IDPosteriorErrorProbability

-in ${param_in}
-out ${param_out}
-out_plot ${param_out_plot}
${param_split_charge}
${param_top_hits_only}
${param_ignore_bad_data}
${param_prob_correct}
-threads \${GALAXY_SLOTS:-24} 
#if $adv_opts.adv_opts_selector=='advanced':
    -smallest_e_value ${adv_opts.param_smallest_e_value}
    -fdr_for_targets_smaller ${adv_opts.param_fdr_for_targets_smaller}
    -fit_algorithm:number_of_bins ${adv_opts.param_number_of_bins}
    -fit_algorithm:incorrectly_assigned ${adv_opts.param_incorrectly_assigned}
#end if
</command>
  <inputs>
    <param name="param_in" type="data" format="idXML" optional="False" label="input file " help="(-in)"/>
    <param name="param_split_charge" type="boolean" truevalue="-split_charge true" falsevalue="-split_charge false" checked="false" optional="True" label="The search engine scores are split by charge if this flag is set. Thus, for each charge state a new model will be computed." help="(-split_charge)"/>
    <param name="param_top_hits_only" type="boolean" truevalue="-top_hits_only true" falsevalue="-top_hits_only false" checked="false" optional="True" label="If set only the top hits of every PeptideIdentification will be used" help="(-top_hits_only)"/>
    <param name="param_ignore_bad_data" type="boolean" truevalue="-ignore_bad_data true" falsevalue="-ignore_bad_data false" checked="false" optional="True" label="If set errors will be written but ignored. Useful for pipelines with many datasets where only a few are bad, but the pipeline should run through." help="(-ignore_bad_data)"/>
    <param name="param_prob_correct" type="boolean" truevalue="-prob_correct true" falsevalue="-prob_correct false" checked="false" optional="True" label="If set scores will be calculated as 1-ErrorProbabilities and can be interpreted as probabilities for correct identifications." help="(-prob_correct)"/>
    <expand macro="advanced_options">
      <param name="param_smallest_e_value" type="float" value="1e-19" label="This value gives a lower bound to E-Values. It should not be 0, as transformation in a real number (log of E-value) is not possible for certain values then." help="(-smallest_e_value)"/>
      <param name="param_fdr_for_targets_smaller" type="float" value="0.05" label="Only used, when top_hits_only set. Additionally, target_decoy information should be available. The score_type must be q-value from an previous False Discovery Rate run." help="(-fdr_for_targets_smaller)"/>
      <param name="param_number_of_bins" type="integer" value="100" label="Number of bins used for visualization. Only needed if each iteration step of the EM-Algorithm will be visualized" help="(-number_of_bins)"/>
      <param name="param_incorrectly_assigned" type="select" optional="True" value="Gumbel" label="for 'Gumbel', the Gumbel distribution is used to plot incorrectly assigned sequences. For 'Gauss', the Gauss distribution is used." help="(-incorrectly_assigned)">
        <option value="Gumbel">Gumbel</option>
        <option value="Gauss">Gauss</option>
      </param>
    </expand>
  </inputs>
  <outputs>
    <data name="param_out" label="output file " format="idXML"/>
    <data name="param_out_plot" label="txt file (if gnuplot is available, a corresponding PDF will be created as well.)" format="txt"/>
  </outputs>
  <help>**What it does**

Estimates probabilities for incorrectly assigned peptide sequences and a set of search engine scores using a mixture model.


For more information, visit http://ftp.mi.fu-berlin.de/OpenMS/release-documentation/html/TOPP_IDPosteriorErrorProbability.html

@REFERENCES@
</help>
</tool>