Mercurial > repos > galaxyp > openms_idposteriorerrorprobability
diff IDPosteriorErrorProbability.xml @ 10:18ee86db4af2 draft
"planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/openms commit 020906fb54bde7fc143c356f41975c378a741315"
| author | galaxyp |
|---|---|
| date | Wed, 09 Sep 2020 20:10:31 +0000 |
| parents | 5d9f175dff81 |
| children | 711a081d80ba |
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--- a/IDPosteriorErrorProbability.xml Fri May 17 10:24:45 2019 -0400 +++ b/IDPosteriorErrorProbability.xml Wed Sep 09 20:10:31 2020 +0000 @@ -1,84 +1,109 @@ <?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="2.3.0"> +<tool id="IDPosteriorErrorProbability" name="IDPosteriorErrorProbability" version="@TOOL_VERSION@+galaxy@GALAXY_VERSION@" profile="20.05"> <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> + <import>macros_autotest.xml</import> + <import>macros_test.xml</import> </macros> - <expand macro="references"/> + <expand macro="requirements"/> <expand macro="stdio"/> - <expand macro="requirements"/> - <command detect_errors="aggressive"><![CDATA[IDPosteriorErrorProbability + <command detect_errors="exit_code"><![CDATA[@QUOTE_FOO@ +@EXT_FOO@ +#import re -#if $param_in: - -in $param_in -#end if -#if $param_out: - -out $param_out -#end if -#if $param_out_plot: - -out_plot $param_out_plot -#end if -#if $param_split_charge: - -split_charge -#end if -#if $param_top_hits_only: - -top_hits_only -#end if -#if $param_ignore_bad_data: - -ignore_bad_data -#end if -#if $param_prob_correct: - -prob_correct -#end if -#if $adv_opts.adv_opts_selector=='advanced': - #if $adv_opts.param_fdr_for_targets_smaller: - -fdr_for_targets_smaller $adv_opts.param_fdr_for_targets_smaller +## Preprocessing +mkdir in && +ln -s '$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 - #if $adv_opts.param_force: - -force -#end if - #if $adv_opts.param_fit_algorithm_number_of_bins: - -fit_algorithm:number_of_bins $adv_opts.param_fit_algorithm_number_of_bins + +## Main program call + +set -o pipefail && +@EXECUTABLE@ -write_ctd ./ && +python3 '$__tool_directory__/fill_ctd.py' '@EXECUTABLE@.ctd' '$args_json' '$hardcoded_json' && +@EXECUTABLE@ -ini @EXECUTABLE@.ctd +-in +'in/${re.sub("[^\w\-_]", "_", $in.element_identifier)}.$gxy2omsext($in.ext)' +-out +'out/output.${gxy2omsext("idxml")}' +#if "out_plot_FLAG" in str($OPTIONAL_OUTPUTS).split(',') + -out_plot + 'out_plot/output.${gxy2omsext("txt")}' #end if - #if $adv_opts.param_fit_algorithm_incorrectly_assigned: - -fit_algorithm:incorrectly_assigned - #if " " in str($adv_opts.param_fit_algorithm_incorrectly_assigned): - "$adv_opts.param_fit_algorithm_incorrectly_assigned" - #else - $adv_opts.param_fit_algorithm_incorrectly_assigned - #end if +#if len(str($OPTIONAL_OUTPUTS).split(',')) == 0 + | tee '$stdout' #end if - #if $adv_opts.param_fit_algorithm_max_nr_iterations: - -fit_algorithm:max_nr_iterations $adv_opts.param_fit_algorithm_max_nr_iterations + +## Postprocessing +&& mv 'out/output.${gxy2omsext("idxml")}' '$out' +#if "out_plot_FLAG" in str($OPTIONAL_OUTPUTS).split(',') + && mv 'out_plot/output.${gxy2omsext("txt")}' '$out_plot' #end if -#end if -]]></command> +#if "ctd_out_FLAG" in $OPTIONAL_OUTPUTS + && mv '@EXECUTABLE@.ctd' '$ctd_out' +#end if]]></command> + <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 name="param_in" type="data" format="idxml" optional="False" label="input file" help="(-in) "/> - <param name="param_split_charge" display="radio" type="boolean" truevalue="-split_charge" falsevalue="" checked="false" optional="True" label="The search engine scores are split by charge if this flag is set" help="(-split_charge) Thus, for each charge state a new model will be computed"/> - <param name="param_top_hits_only" display="radio" type="boolean" truevalue="-top_hits_only" falsevalue="" 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" display="radio" type="boolean" truevalue="-ignore_bad_data" falsevalue="" checked="false" optional="True" label="If set errors will be written but ignored" help="(-ignore_bad_data) Useful for pipelines with many datasets where only a few are bad, but the pipeline should run through"/> - <param name="param_prob_correct" display="radio" type="boolean" truevalue="-prob_correct" falsevalue="" 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_fdr_for_targets_smaller" type="float" value="0.05" label="Only used, when top_hits_only set" help="(-fdr_for_targets_smaller) Additionally, target/decoy information should be available. The score_type must be q-value from an previous False Discovery Rate run"/> - <param name="param_force" display="radio" type="boolean" truevalue="-force" falsevalue="" checked="false" optional="True" label="Overwrite tool specific checks" help="(-force) "/> - <param name="param_fit_algorithm_number_of_bins" type="integer" value="100" label="Number of bins used for visualization" help="(-number_of_bins) Only needed if each iteration step of the EM-Algorithm will be visualized"/> - <param name="param_fit_algorithm_incorrectly_assigned" display="radio" type="select" optional="False" value="Gumbel" label="for 'Gumbel', the Gumbel distribution is used to plot incorrectly assigned sequences" help="(-incorrectly_assigned) For 'Gauss', the Gauss distribution is used"> + <param name="in" argument="-in" type="data" format="idxml" optional="false" label="input file" help=" select idxml data sets(s)"/> + <param name="split_charge" 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 name="top_hits_only" 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 name="ignore_bad_data" 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 name="prob_correct" 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" display="radio" type="select" optional="false" 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"/> </param> - <param name="param_fit_algorithm_max_nr_iterations" type="integer" value="1000" label="Bounds the number of iterations for the EM algorithm when convergence is slow" help="(-max_nr_iterations) "/> + <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" display="radio" type="select" optional="false" 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"/> + </param> + </section> + <expand macro="adv_opts_macro"> + <param name="fdr_for_targets_smaller" 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 name="force" argument="-force" type="boolean" truevalue="true" falsevalue="false" checked="false" label="Overwrite tool specific checks" help=""/> + <param name="test" argument="-test" type="hidden" optional="true" value="False" label="Enables the test mode (needed for internal use only)" help=""> + <expand macro="list_string_san"/> + </param> </expand> + <param name="OPTIONAL_OUTPUTS" type="select" multiple="true" label="Optional outputs" optional="true"> + <option value="out_plot_FLAG">out_plot (What to do with outliers:)</option> + <option value="ctd_out_FLAG">Output used ctd (ini) configuration file</option> + </param> </inputs> <outputs> - <data name="param_out" format="idxml"/> - <data name="param_out_plot" format="txt"/> + <data name="out" label="${tool.name} on ${on_string}: out" format="idxml"/> + <data name="out_plot" label="${tool.name} on ${on_string}: out_plot" format="txt"> + <filter>OPTIONAL_OUTPUTS is not None and "out_plot_FLAG" in OPTIONAL_OUTPUTS</filter> + </data> + <data name="ctd_out" format="xml" label="${tool.name} on ${on_string}: ctd"> + <filter>OPTIONAL_OUTPUTS is not None and "ctd_out_FLAG" in OPTIONAL_OUTPUTS</filter> + </data> </outputs> - <help>Estimates probabilities for incorrectly assigned peptide sequences and a set of search engine scores using a mixture model. + <tests> + <expand macro="autotest_IDPosteriorErrorProbability"/> + <expand macro="manutest_IDPosteriorErrorProbability"/> + </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://abibuilder.informatik.uni-tuebingen.de/archive/openms/Documentation/release/2.3.0/html/TOPP_IDPosteriorErrorProbability.html</help> +For more information, visit http://www.openms.de/documentation/TOPP_IDPosteriorErrorProbability.html]]></help> + <expand macro="references"/> </tool>