comparison IDPosteriorErrorProbability.xml @ 15:93e6ec445d5d draft default tip

planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/openms commit 5c080b1e2b99f1c88f4557e9fec8c45c9d23b906

14:986e03d3201e

<?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 CTDConverter.-->
<!--Proposed Tool Section: [ID Processing]-->
<tool id="IDPosteriorErrorProbability" name="IDPosteriorErrorProbability" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="21.05">
  <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="requirements"/>

@EXT_FOO@
#import re

## Preprocessing
mkdir in &&
ln -s '$in' 'in/${re.sub("[^\w\-_]", "_", $in.element_identifier)}.$gxy2omsext($in.ext)' &&
mkdir out &&
#if "out_plot_FLAG" in str($OPTIONAL_OUTPUTS).split(',')
  mkdir out_plot &&
#end if

  <configfiles>
    <inputs name="args_json" data_style="paths"/>
    <configfile name="hardcoded_json"><![CDATA[{"log": "log.txt", "threads": "\${GALAXY_SLOTS:-1}", "no_progress": true}]]></configfile>
  </configfiles>
  <inputs>
    <param argument="-in" type="data" format="idxml" optional="false" label="input file" help=" select idxml data sets(s)"/>
    <param argument="-split_charge" type="boolean" truevalue="true" falsevalue="false" checked="false" label="The search engine scores are split by charge if this flag is set" help="Thus, for each charge state a new model will be computed"/>
    <param argument="-top_hits_only" type="boolean" truevalue="true" falsevalue="false" checked="false" label="If set only the top hits of every PeptideIdentification will be used" help=""/>
    <param argument="-ignore_bad_data" type="boolean" truevalue="true" falsevalue="false" checked="false" label="If set errors will be written but ignored" help="Useful for pipelines with many datasets where only a few are bad, but the pipeline should run through"/>
    <param argument="-prob_correct" type="boolean" truevalue="true" falsevalue="false" checked="false" label="If set scores will be calculated as '1 - ErrorProbabilities' and can be interpreted as probabilities for correct identifications" help=""/>
    <section name="fit_algorithm" title="Algorithm parameter subsection" help="" expanded="false">
      <param name="number_of_bins" argument="-fit_algorithm:number_of_bins" type="integer" optional="true" value="100" label="Number of bins used for visualization" help="Only needed if each iteration step of the EM-Algorithm will be visualized"/>
      <param name="incorrectly_assigned" argument="-fit_algorithm:incorrectly_assigned" type="select" optional="true" label="for 'Gumbel', the Gumbel distribution is used to plot incorrectly assigned sequences" help="For 'Gauss', the Gauss distribution is used">
        <option value="Gumbel" selected="true">Gumbel</option>
        <option value="Gauss">Gauss</option>
        <expand macro="list_string_san" name="incorrectly_assigned"/>
      </param>
      <param name="max_nr_iterations" argument="-fit_algorithm:max_nr_iterations" type="integer" optional="true" value="1000" label="Bounds the number of iterations for the EM algorithm when convergence is slow" help=""/>
      <param name="neg_log_delta" argument="-fit_algorithm:neg_log_delta" type="integer" optional="true" value="6" label="The negative logarithm of the convergence threshold for the likelihood increase" help=""/>
      <param name="outlier_handling" argument="-fit_algorithm:outlier_handling" type="select" optional="true" label="What to do with outliers:" help="- ignore_iqr_outliers: ignore outliers outside of 3*IQR from Q1/Q3 for fitting. - set_iqr_to_closest_valid: set IQR-based outliers to the last valid value for fitting. - ignore_extreme_percentiles: ignore everything outside 99th and 1st percentile (also removes equal values like potential censored max values in XTandem). - none: do nothing">
        <option value="ignore_iqr_outliers" selected="true">ignore_iqr_outliers</option>
        <option value="set_iqr_to_closest_valid">set_iqr_to_closest_valid</option>
        <option value="ignore_extreme_percentiles">ignore_extreme_percentiles</option>
        <option value="none">none</option>
        <expand macro="list_string_san" name="outlier_handling"/>
      </param>
    </section>
    <expand macro="adv_opts_macro">
      <param argument="-fdr_for_targets_smaller" type="float" optional="true" value="0.05" label="Only used, when top_hits_only set" help="Additionally, target/decoy information should be available. The score_type must be q-value from an previous False Discovery Rate run"/>
      <param argument="-force" type="boolean" truevalue="true" falsevalue="false" checked="false" label="Overrides tool-specific checks" help=""/>
      <param argument="-test" type="hidden" optional="true" value="False" label="Enables the test mode (needed for internal use only)" help="">
        <expand macro="list_string_san" name="test"/>
      </param>
    </expand>
    <param name="OPTIONAL_OUTPUTS" type="select" optional="true" multiple="true" label="Optional outputs">
      <option value="out_plot_FLAG">out_plot (txt file (if gnuplot is available, a corresponding PDF will be created as well.))</option>

    </data>
    <data name="ctd_out" format="xml" label="${tool.name} on ${on_string}: ctd">
      <filter>OPTIONAL_OUTPUTS is not None and "ctd_out_FLAG" in OPTIONAL_OUTPUTS</filter>
    </data>
  </outputs>
  <tests><!-- TOPP_IDPosteriorErrorProbability_1 -->
    <test expect_num_outputs="2">
      <section name="adv_opts">
        <param name="fdr_for_targets_smaller" value="0.05"/>
        <param name="force" value="false"/>
        <param name="test" value="true"/>
      </section>
      <param name="in" value="IDPosteriorErrorProbability_Mascot_input.idXML"/>
      <output name="out" file="IDPosteriorErrorProbability_Mascot_output.idXML" compare="sim_size" delta_frac="0.7" ftype="idxml"/>
      <param name="split_charge" value="false"/>
      <param name="top_hits_only" value="false"/>
      <param name="ignore_bad_data" value="false"/>
      <param name="prob_correct" value="false"/>
      <section name="fit_algorithm">
        <param name="number_of_bins" value="100"/>
        <param name="incorrectly_assigned" value="Gumbel"/>
        <param name="max_nr_iterations" value="1000"/>
        <param name="neg_log_delta" value="6"/>
        <param name="outlier_handling" value="ignore_iqr_outliers"/>
      </section>
      <param name="OPTIONAL_OUTPUTS" value="ctd_out_FLAG"/>
      <output name="ctd_out" ftype="xml">
        <assert_contents>
          <is_valid_xml/>
        </assert_contents>
      </output>
    </test>
    <!-- TOPP_IDPosteriorErrorProbability_2 -->
    <test expect_num_outputs="2">
      <section name="adv_opts">
        <param name="fdr_for_targets_smaller" value="0.05"/>
        <param name="force" value="false"/>
        <param name="test" value="true"/>
      </section>
      <param name="in" value="IDPosteriorErrorProbability_XTandem_input.idXML"/>
      <output name="out" file="IDPosteriorErrorProbability_XTandem_output.idXML" compare="sim_size" delta_frac="0.7" ftype="idxml"/>
      <param name="split_charge" value="false"/>
      <param name="top_hits_only" value="false"/>
      <param name="ignore_bad_data" value="false"/>
      <param name="prob_correct" value="false"/>
      <section name="fit_algorithm">
        <param name="number_of_bins" value="100"/>
        <param name="incorrectly_assigned" value="Gumbel"/>
        <param name="max_nr_iterations" value="1000"/>
        <param name="neg_log_delta" value="6"/>
        <param name="outlier_handling" value="ignore_iqr_outliers"/>
      </section>
      <param name="OPTIONAL_OUTPUTS" value="ctd_out_FLAG"/>
      <output name="ctd_out" ftype="xml">
        <assert_contents>
          <is_valid_xml/>
        </assert_contents>
      </output>
    </test>
    <!-- TOPP_IDPosteriorErrorProbability_3 -->
    <test expect_num_outputs="2">
      <section name="adv_opts">
        <param name="fdr_for_targets_smaller" value="0.05"/>
        <param name="force" value="false"/>
        <param name="test" value="true"/>
      </section>
      <param name="in" value="IDPosteriorErrorProbability_OMSSA_input.idXML"/>
      <output name="out" file="IDPosteriorErrorProbability_OMSSA_output.idXML" compare="sim_size" delta_frac="0.7" ftype="idxml"/>
      <param name="split_charge" value="false"/>
      <param name="top_hits_only" value="false"/>
      <param name="ignore_bad_data" value="false"/>
      <param name="prob_correct" value="false"/>
      <section name="fit_algorithm">
        <param name="number_of_bins" value="100"/>
        <param name="incorrectly_assigned" value="Gumbel"/>
        <param name="max_nr_iterations" value="1000"/>
        <param name="neg_log_delta" value="6"/>
        <param name="outlier_handling" value="ignore_iqr_outliers"/>
      </section>
      <param name="OPTIONAL_OUTPUTS" value="ctd_out_FLAG"/>
      <output name="ctd_out" ftype="xml">
        <assert_contents>
          <is_valid_xml/>
        </assert_contents>
      </output>
    </test>
    <!-- TOPP_IDPosteriorErrorProbability_4 -->
    <test expect_num_outputs="2">
      <section name="adv_opts">
        <param name="fdr_for_targets_smaller" value="0.05"/>
        <param name="force" value="false"/>
        <param name="test" value="true"/>
      </section>
      <param name="in" value="IDPosteriorErrorProbability_OMSSA_input2.idXML"/>
      <output name="out" file="IDPosteriorErrorProbability_OMSSA_output2.idXML" compare="sim_size" delta_frac="0.7" ftype="idxml"/>
      <param name="split_charge" value="true"/>
      <param name="top_hits_only" value="false"/>
      <param name="ignore_bad_data" value="false"/>
      <param name="prob_correct" value="false"/>
      <section name="fit_algorithm">

      <output name="ctd_out" ftype="xml">
        <assert_contents>
          <is_valid_xml/>
        </assert_contents>
      </output>
    </test>
    <!-- TOPP_IDPosteriorErrorProbability_5 -->
    <test expect_num_outputs="2">
      <section name="adv_opts">
        <param name="fdr_for_targets_smaller" value="0.05"/>
        <param name="force" value="false"/>
        <param name="test" value="true"/>
      </section>
      <param name="in" value="IDPosteriorErrorProbability_XTandem_input2.idXML"/>
      <output name="out" file="IDPosteriorErrorProbability_XTandem_output2.idXML" compare="sim_size" delta_frac="0.7" ftype="idxml"/>
      <param name="split_charge" value="true"/>
      <param name="top_hits_only" value="false"/>
      <param name="ignore_bad_data" value="false"/>
      <param name="prob_correct" value="false"/>
      <section name="fit_algorithm">

      <output name="ctd_out" ftype="xml">
        <assert_contents>
          <is_valid_xml/>
        </assert_contents>
      </output>
    </test>
    <!-- TOPP_IDPosteriorErrorProbability_6 -->
    <test expect_num_outputs="2">
      <section name="adv_opts">
        <param name="fdr_for_targets_smaller" value="0.05"/>
        <param name="force" value="false"/>
        <param name="test" value="true"/>
      </section>
      <param name="in" value="IDPosteriorErrorProbability_Mascot_input2.idXML"/>
      <output name="out" file="IDPosteriorErrorProbability_Mascot_output2.idXML" compare="sim_size" delta_frac="0.7" ftype="idxml"/>
      <param name="split_charge" value="true"/>
      <param name="top_hits_only" value="false"/>
      <param name="ignore_bad_data" value="false"/>
      <param name="prob_correct" value="false"/>
      <section name="fit_algorithm">

      <output name="ctd_out" ftype="xml">
        <assert_contents>
          <is_valid_xml/>
        </assert_contents>
      </output>
    </test>
    <!-- TOPP_IDPosteriorErrorProbability_7 -->
    <test expect_num_outputs="2">
      <section name="adv_opts">
        <param name="fdr_for_targets_smaller" value="0.05"/>
        <param name="force" value="false"/>
        <param name="test" value="true"/>
      </section>
      <param name="in" value="IDPosteriorErrorProbability_bad_data.idXML"/>
      <output name="out" file="IDPosteriorErrorProbability_bad_data_out.idXML" compare="sim_size" delta_frac="0.7" ftype="idxml"/>
      <param name="split_charge" value="false"/>
      <param name="top_hits_only" value="false"/>
      <param name="ignore_bad_data" value="true"/>
      <param name="prob_correct" value="false"/>
      <section name="fit_algorithm">

      <output name="ctd_out" ftype="xml">
        <assert_contents>
          <is_valid_xml/>
        </assert_contents>
      </output>
    </test>
    <!-- TOPP_IDPosteriorErrorProbability_8 -->
    <test expect_num_outputs="2">
      <section name="adv_opts">
        <param name="fdr_for_targets_smaller" value="0.05"/>
        <param name="force" value="false"/>
        <param name="test" value="true"/>
      </section>
      <param name="in" value="IDPosteriorErrorProbability_OMSSA_input.idXML"/>
      <output name="out" file="IDPosteriorErrorProbability_prob_correct_output.idXML" compare="sim_size" delta_frac="0.7" ftype="idxml"/>
      <param name="split_charge" value="false"/>
      <param name="top_hits_only" value="false"/>
      <param name="ignore_bad_data" value="false"/>
      <param name="prob_correct" value="true"/>
      <section name="fit_algorithm">

      <output name="ctd_out" ftype="xml">
        <assert_contents>
          <is_valid_xml/>
        </assert_contents>
      </output>
    </test>
  </tests>
  <help><![CDATA[Estimates probabilities for incorrectly assigned peptide sequences and a set of search engine scores using a mixture model.


For more information, visit http://www.openms.de/doxygen/release/2.8.0/html/TOPP_IDPosteriorErrorProbability.html]]></help>
  <expand macro="references"/>
</tool>

15:93e6ec445d5d

<!--This is a configuration file for the integration of a tools into Galaxy (https://galaxyproject.org/). This file was automatically generated using CTDConverter.-->
<!--Proposed Tool Section: [Identification Processing]-->
<tool id="IDPosteriorErrorProbability" name="IDPosteriorErrorProbability" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="21.05">
  <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="requirements"/>

@EXT_FOO@
#import re

## Preprocessing
mkdir in &&
cp '$in' 'in/${re.sub("[^\w\-_]", "_", $in.element_identifier)}.$gxy2omsext($in.ext)' &&
mkdir out &&
#if "out_plot_FLAG" in str($OPTIONAL_OUTPUTS).split(',')
  mkdir out_plot &&
#end if

  <configfiles>
    <inputs name="args_json" data_style="paths"/>
    <configfile name="hardcoded_json"><![CDATA[{"log": "log.txt", "threads": "\${GALAXY_SLOTS:-1}", "no_progress": true}]]></configfile>
  </configfiles>
  <inputs>
    <param argument="-in" type="data" format="idxml" label="input file" help=" select idxml data sets(s)"/>
    <param argument="-split_charge" type="boolean" truevalue="true" falsevalue="false" checked="false" label="The search engine scores are split by charge if this flag is set" help="Thus, for each charge state a new model will be computed"/>
    <param argument="-top_hits_only" type="boolean" truevalue="true" falsevalue="false" checked="false" label="If set only the top hits of every PeptideIdentification will be used" help=""/>
    <param argument="-ignore_bad_data" type="boolean" truevalue="true" falsevalue="false" checked="false" label="If set errors will be written but ignored" help="Useful for pipelines with many datasets where only a few are bad, but the pipeline should run through"/>
    <param argument="-prob_correct" type="boolean" truevalue="true" falsevalue="false" checked="false" label="If set scores will be calculated as '1 - ErrorProbabilities' and can be interpreted as probabilities for correct identifications" help=""/>
    <section name="fit_algorithm" title="Algorithm parameter subsection" help="" expanded="false">
      <param name="number_of_bins" argument="-fit_algorithm:number_of_bins" type="integer" value="100" label="Number of bins used for visualization" help="Only needed if each iteration step of the EM-Algorithm will be visualized"/>
      <param name="incorrectly_assigned" argument="-fit_algorithm:incorrectly_assigned" type="select" label="for 'Gumbel', the Gumbel distribution is used to plot incorrectly assigned sequences" help="For 'Gauss', the Gauss distribution is used">
        <option value="Gumbel" selected="true">Gumbel</option>
        <option value="Gauss">Gauss</option>
        <expand macro="list_string_san" name="incorrectly_assigned"/>
      </param>
      <param name="max_nr_iterations" argument="-fit_algorithm:max_nr_iterations" type="integer" value="1000" label="Bounds the number of iterations for the EM algorithm when convergence is slow" help=""/>
      <param name="neg_log_delta" argument="-fit_algorithm:neg_log_delta" type="integer" value="6" label="The negative logarithm of the convergence threshold for the likelihood increase" help=""/>
      <param name="outlier_handling" argument="-fit_algorithm:outlier_handling" type="select" label="What to do with outliers:" help="- ignore_iqr_outliers: ignore outliers outside of 3*IQR from Q1/Q3 for fitting. - set_iqr_to_closest_valid: set IQR-based outliers to the last valid value for fitting. - ignore_extreme_percentiles: ignore everything outside 99th and 1st percentile (also removes equal values like potential censored max values in XTandem). - none: do nothing">
        <option value="ignore_iqr_outliers" selected="true">ignore_iqr_outliers</option>
        <option value="set_iqr_to_closest_valid">set_iqr_to_closest_valid</option>
        <option value="ignore_extreme_percentiles">ignore_extreme_percentiles</option>
        <option value="none">none</option>
        <expand macro="list_string_san" name="outlier_handling"/>
      </param>
    </section>
    <expand macro="adv_opts_macro">
      <param argument="-fdr_for_targets_smaller" type="float" value="0.05" label="Only used, when top_hits_only set" help="Additionally, target/decoy information should be available. The score_type must be q-value from an previous False Discovery Rate run"/>
      <param argument="-force" type="boolean" truevalue="true" falsevalue="false" checked="false" label="Overrides tool-specific checks" help=""/>
      <param argument="-test" type="hidden" value="False" label="Enables the test mode (needed for internal use only)" help="" optional="true">
        <expand macro="list_string_san" name="test"/>
      </param>
    </expand>
    <param name="OPTIONAL_OUTPUTS" type="select" optional="true" multiple="true" label="Optional outputs">
      <option value="out_plot_FLAG">out_plot (txt file (if gnuplot is available, a corresponding PDF will be created as well.))</option>

    </data>
    <data name="ctd_out" format="xml" label="${tool.name} on ${on_string}: ctd">
      <filter>OPTIONAL_OUTPUTS is not None and "ctd_out_FLAG" in OPTIONAL_OUTPUTS</filter>
    </data>
  </outputs>
  <tests>
    <!-- TOPP_IDPosteriorErrorProbability_1 -->
    <test expect_num_outputs="2">
      <section name="adv_opts">
        <param name="fdr_for_targets_smaller" value="0.05"/>
        <param name="force" value="false"/>
        <param name="test" value="true"/>
      </section>
      <param name="in" value="IDPosteriorErrorProbability_Mascot_input.idXML"/>
      <output name="out" value="IDPosteriorErrorProbability_Mascot_output.idXML" compare="sim_size" delta_frac="0.7" ftype="idxml"/>
      <param name="split_charge" value="false"/>
      <param name="top_hits_only" value="false"/>
      <param name="ignore_bad_data" value="false"/>
      <param name="prob_correct" value="false"/>
      <section name="fit_algorithm">
        <param name="number_of_bins" value="100"/>
        <param name="incorrectly_assigned" value="Gumbel"/>
        <param name="max_nr_iterations" value="1000"/>
        <param name="neg_log_delta" value="6"/>
        <param name="outlier_handling" value="ignore_iqr_outliers"/>
      </section>
      <param name="OPTIONAL_OUTPUTS" value="ctd_out_FLAG"/>
      <output name="ctd_out" ftype="xml">
        <assert_contents>
          <is_valid_xml/>
        </assert_contents>
      </output>
      <assert_stdout>
        <has_text_matching expression="@EXECUTABLE@ took .* \(wall\), .* \(CPU\), .* \(system\), .* \(user\)(; Peak Memory Usage: 32 MB)?."/>
      </assert_stdout>
    </test>
    <!-- TOPP_IDPosteriorErrorProbability_2 -->
    <test expect_num_outputs="2">
      <section name="adv_opts">
        <param name="fdr_for_targets_smaller" value="0.05"/>
        <param name="force" value="false"/>
        <param name="test" value="true"/>
      </section>
      <param name="in" value="IDPosteriorErrorProbability_XTandem_input.idXML"/>
      <output name="out" value="IDPosteriorErrorProbability_XTandem_output.idXML" compare="sim_size" delta_frac="0.7" ftype="idxml"/>
      <param name="split_charge" value="false"/>
      <param name="top_hits_only" value="false"/>
      <param name="ignore_bad_data" value="false"/>
      <param name="prob_correct" value="false"/>
      <section name="fit_algorithm">
        <param name="number_of_bins" value="100"/>
        <param name="incorrectly_assigned" value="Gumbel"/>
        <param name="max_nr_iterations" value="1000"/>
        <param name="neg_log_delta" value="6"/>
        <param name="outlier_handling" value="ignore_iqr_outliers"/>
      </section>
      <param name="OPTIONAL_OUTPUTS" value="ctd_out_FLAG"/>
      <output name="ctd_out" ftype="xml">
        <assert_contents>
          <is_valid_xml/>
        </assert_contents>
      </output>
      <assert_stdout>
        <has_text_matching expression="@EXECUTABLE@ took .* \(wall\), .* \(CPU\), .* \(system\), .* \(user\)(; Peak Memory Usage: 32 MB)?."/>
      </assert_stdout>
    </test>
    <!-- TOPP_IDPosteriorErrorProbability_3 -->
    <test expect_num_outputs="2">
      <section name="adv_opts">
        <param name="fdr_for_targets_smaller" value="0.05"/>
        <param name="force" value="false"/>
        <param name="test" value="true"/>
      </section>
      <param name="in" value="IDPosteriorErrorProbability_OMSSA_input.idXML"/>
      <output name="out" value="IDPosteriorErrorProbability_OMSSA_output.idXML" compare="sim_size" delta_frac="0.7" ftype="idxml"/>
      <param name="split_charge" value="false"/>
      <param name="top_hits_only" value="false"/>
      <param name="ignore_bad_data" value="false"/>
      <param name="prob_correct" value="false"/>
      <section name="fit_algorithm">
        <param name="number_of_bins" value="100"/>
        <param name="incorrectly_assigned" value="Gumbel"/>
        <param name="max_nr_iterations" value="1000"/>
        <param name="neg_log_delta" value="6"/>
        <param name="outlier_handling" value="ignore_iqr_outliers"/>
      </section>
      <param name="OPTIONAL_OUTPUTS" value="ctd_out_FLAG"/>
      <output name="ctd_out" ftype="xml">
        <assert_contents>
          <is_valid_xml/>
        </assert_contents>
      </output>
      <assert_stdout>
        <has_text_matching expression="@EXECUTABLE@ took .* \(wall\), .* \(CPU\), .* \(system\), .* \(user\)(; Peak Memory Usage: 32 MB)?."/>
      </assert_stdout>
    </test>
    <!-- TOPP_IDPosteriorErrorProbability_4 -->
    <test expect_num_outputs="2">
      <section name="adv_opts">
        <param name="fdr_for_targets_smaller" value="0.05"/>
        <param name="force" value="false"/>
        <param name="test" value="true"/>
      </section>
      <param name="in" value="IDPosteriorErrorProbability_OMSSA_input2.idXML"/>
      <output name="out" value="IDPosteriorErrorProbability_OMSSA_output2.idXML" compare="sim_size" delta_frac="0.7" ftype="idxml"/>
      <param name="split_charge" value="true"/>
      <param name="top_hits_only" value="false"/>
      <param name="ignore_bad_data" value="false"/>
      <param name="prob_correct" value="false"/>
      <section name="fit_algorithm">

      <output name="ctd_out" ftype="xml">
        <assert_contents>
          <is_valid_xml/>
        </assert_contents>
      </output>
      <assert_stdout>
        <has_text_matching expression="@EXECUTABLE@ took .* \(wall\), .* \(CPU\), .* \(system\), .* \(user\)(; Peak Memory Usage: 32 MB)?."/>
      </assert_stdout>
    </test>
    <!-- TOPP_IDPosteriorErrorProbability_5 -->
    <test expect_num_outputs="2">
      <section name="adv_opts">
        <param name="fdr_for_targets_smaller" value="0.05"/>
        <param name="force" value="false"/>
        <param name="test" value="true"/>
      </section>
      <param name="in" value="IDPosteriorErrorProbability_XTandem_input2.idXML"/>
      <output name="out" value="IDPosteriorErrorProbability_XTandem_output2.idXML" compare="sim_size" delta_frac="0.7" ftype="idxml"/>
      <param name="split_charge" value="true"/>
      <param name="top_hits_only" value="false"/>
      <param name="ignore_bad_data" value="false"/>
      <param name="prob_correct" value="false"/>
      <section name="fit_algorithm">

      <output name="ctd_out" ftype="xml">
        <assert_contents>
          <is_valid_xml/>
        </assert_contents>
      </output>
      <assert_stdout>
        <has_text_matching expression="@EXECUTABLE@ took .* \(wall\), .* \(CPU\), .* \(system\), .* \(user\)(; Peak Memory Usage: 32 MB)?."/>
      </assert_stdout>
    </test>
    <!-- TOPP_IDPosteriorErrorProbability_6 -->
    <test expect_num_outputs="2">
      <section name="adv_opts">
        <param name="fdr_for_targets_smaller" value="0.05"/>
        <param name="force" value="false"/>
        <param name="test" value="true"/>
      </section>
      <param name="in" value="IDPosteriorErrorProbability_Mascot_input2.idXML"/>
      <output name="out" value="IDPosteriorErrorProbability_Mascot_output2.idXML" compare="sim_size" delta_frac="0.7" ftype="idxml"/>
      <param name="split_charge" value="true"/>
      <param name="top_hits_only" value="false"/>
      <param name="ignore_bad_data" value="false"/>
      <param name="prob_correct" value="false"/>
      <section name="fit_algorithm">

      <output name="ctd_out" ftype="xml">
        <assert_contents>
          <is_valid_xml/>
        </assert_contents>
      </output>
      <assert_stdout>
        <has_text_matching expression="@EXECUTABLE@ took .* \(wall\), .* \(CPU\), .* \(system\), .* \(user\)(; Peak Memory Usage: 32 MB)?."/>
      </assert_stdout>
    </test>
    <!-- TOPP_IDPosteriorErrorProbability_7 -->
    <test expect_num_outputs="2">
      <section name="adv_opts">
        <param name="fdr_for_targets_smaller" value="0.05"/>
        <param name="force" value="false"/>
        <param name="test" value="true"/>
      </section>
      <param name="in" value="IDPosteriorErrorProbability_bad_data.idXML"/>
      <output name="out" value="IDPosteriorErrorProbability_bad_data_output.tmp" compare="sim_size" delta_frac="0.7" ftype="idxml"/>
      <param name="split_charge" value="false"/>
      <param name="top_hits_only" value="false"/>
      <param name="ignore_bad_data" value="true"/>
      <param name="prob_correct" value="false"/>
      <section name="fit_algorithm">

      <output name="ctd_out" ftype="xml">
        <assert_contents>
          <is_valid_xml/>
        </assert_contents>
      </output>
      <assert_stdout>
        <has_text_matching expression="@EXECUTABLE@ took .* \(wall\), .* \(CPU\), .* \(system\), .* \(user\)(; Peak Memory Usage: 32 MB)?."/>
      </assert_stdout>
    </test>
    <!-- TOPP_IDPosteriorErrorProbability_8 -->
    <test expect_num_outputs="2">
      <section name="adv_opts">
        <param name="fdr_for_targets_smaller" value="0.05"/>
        <param name="force" value="false"/>
        <param name="test" value="true"/>
      </section>
      <param name="in" value="IDPosteriorErrorProbability_OMSSA_input.idXML"/>
      <output name="out" value="IDPosteriorErrorProbability_prob_correct_output.idXML" compare="sim_size" delta_frac="0.7" ftype="idxml"/>
      <param name="split_charge" value="false"/>
      <param name="top_hits_only" value="false"/>
      <param name="ignore_bad_data" value="false"/>
      <param name="prob_correct" value="true"/>
      <section name="fit_algorithm">

      <output name="ctd_out" ftype="xml">
        <assert_contents>
          <is_valid_xml/>
        </assert_contents>
      </output>
      <assert_stdout>
        <has_text_matching expression="@EXECUTABLE@ took .* \(wall\), .* \(CPU\), .* \(system\), .* \(user\)(; Peak Memory Usage: 32 MB)?."/>
      </assert_stdout>
    </test>
  </tests>
  <help><![CDATA[Estimates probabilities for incorrectly assigned peptide sequences and a set of search engine scores using a mixture model.


For more information, visit https://openms.de/doxygen/release/3.1.0/html/TOPP_IDPosteriorErrorProbability.html]]></help>
  <expand macro="references"/>
</tool>