Mercurial > repos > galaxyp > openms_percolatoradapter
view PercolatorAdapter.xml @ 2:4ed4e0b7f57c draft
planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/openms commit f608f41d45664d04d3124c6ebc791bf8a566b3c5
author | galaxyp |
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date | Wed, 15 May 2019 08:20:02 -0400 |
parents | 0e7bb87aa55c |
children | e7881a82b56d |
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<?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="PercolatorAdapter" name="PercolatorAdapter" version="2.3.0"> <description>Facilitate input to Percolator and reintegrate.</description> <macros> <token name="@EXECUTABLE@">PercolatorAdapter</token> <import>macros.xml</import> </macros> <expand macro="references"/> <expand macro="stdio"/> <expand macro="requirements"/> <command detect_errors="aggressive"><![CDATA[PercolatorAdapter -in #for token in $param_in: $token #end for -in_decoy #for token in $param_in_decoy: $token #end for #if $param_out: -out $param_out #end if #if $param_mzid_out: -mzid_out $param_mzid_out #end if #if $param_enzyme: -enzyme #if " " in str($param_enzyme): "$param_enzyme" #else $param_enzyme #end if #end if #if $param_percolator_executable: -percolator_executable $param_percolator_executable #end if #if $param_peptide_level_fdrs: -peptide-level-fdrs #end if #if $param_protein_level_fdrs: -protein-level-fdrs #end if #if $param_weights: -weights $param_weights #end if #if $adv_opts.adv_opts_selector=='advanced': #if $adv_opts.param_generic_feature_set: -generic-feature-set #end if #if $adv_opts.param_subset_max_train: -subset-max-train $adv_opts.param_subset_max_train #end if #if $adv_opts.param_cpos: -cpos $adv_opts.param_cpos #end if #if $adv_opts.param_cneg: -cneg $adv_opts.param_cneg #end if #if $adv_opts.param_testFDR: -testFDR $adv_opts.param_testFDR #end if #if $adv_opts.param_trainFDR: -trainFDR $adv_opts.param_trainFDR #end if #if $adv_opts.param_maxiter: -maxiter $adv_opts.param_maxiter #end if #if $adv_opts.param_quick_validation: -quick-validation #end if #if $adv_opts.param_init_weights: -init-weights $adv_opts.param_init_weights #end if #if $adv_opts.param_default_direction: -default-direction "$adv_opts.param_default_direction" #end if #if $adv_opts.param_verbose: -verbose $adv_opts.param_verbose #end if #if $adv_opts.param_unitnorm: -unitnorm #end if #if $adv_opts.param_test_each_iteration: -test-each-iteration #end if #if $adv_opts.param_override: -override #end if #if $adv_opts.param_seed: -seed $adv_opts.param_seed #end if #if $adv_opts.param_doc: -doc $adv_opts.param_doc #end if #if $adv_opts.param_klammer: -klammer #end if #if $adv_opts.param_fasta: -fasta $adv_opts.param_fasta #end if #if $adv_opts.param_decoy_pattern: -decoy-pattern "$adv_opts.param_decoy_pattern" #end if #if $adv_opts.param_post_processing_tdc: -post-processing-tdc #end if #if $adv_opts.param_force: -force #end if #end if ]]></command> <inputs> <param name="param_in" type="data" format="mzid,idxml" multiple="true" optional="False" size="30" label="Input file(s)" help="(-in) "> <sanitizer> <valid initial="string.printable"> <remove value="'"/> <remove value="""/> </valid> </sanitizer> </param> <param name="param_in_decoy" type="data" format="mzid,idxml" multiple="true" optional="True" size="30" label="Input decoy file(s) in case of separate searches" help="(-in_decoy) "> <sanitizer> <valid initial="string.printable"> <remove value="'"/> <remove value="""/> </valid> </sanitizer> </param> <param name="param_enzyme" type="select" optional="False" value="trypsin" label="Type of enzyme: no_enzyme,elastase,pepsin,proteinasek,thermolysin,chymotrypsin,lys-n,lys-c,arg-c,asp-n,glu-c,trypsin" help="(-enzyme) "> <option value="no_enzyme">no_enzyme</option> <option value="elastase">elastase</option> <option value="pepsin">pepsin</option> <option value="proteinasek">proteinasek</option> <option value="thermolysin">thermolysin</option> <option value="chymotrypsin">chymotrypsin</option> <option value="lys-n">lys-n</option> <option value="lys-c">lys-c</option> <option value="arg-c">arg-c</option> <option value="asp-n">asp-n</option> <option value="glu-c">glu-c</option> <option value="trypsin" selected="true">trypsin</option> </param> <param name="param_percolator_executable" type="data" format="txt" value="percolator" label="Percolator executable of the installation" help="(-percolator_executable) e.g. 'percolator.exe'"/> <param name="param_peptide_level_fdrs" display="radio" type="boolean" truevalue="-peptide-level-fdrs" falsevalue="" checked="false" optional="True" label="Calculate peptide-level FDRs instead of PSM-level FDRs" help="(-peptide-level-fdrs) "/> <param name="param_protein_level_fdrs" display="radio" type="boolean" truevalue="-protein-level-fdrs" falsevalue="" checked="false" optional="True" label="Use the picked protein-level FDR to infer protein probabilities" help="(-protein-level-fdrs) Use the -fasta option and -decoy-pattern to set the Fasta file and decoy pattern"/> <expand macro="advanced_options"> <param name="param_generic_feature_set" display="radio" type="boolean" truevalue="-generic-feature-set" falsevalue="" checked="false" optional="True" label="Use only generic (i.e" help="(-generic-feature-set) not search engine specific) features. Generating search engine specific features for common search engines by PSMFeatureExtractor will typically boost the identification rate significantly"/> <param name="param_subset_max_train" type="integer" value="0" label="Only train an SVM on a subset of <x> PSMs, and use the resulting score vector to evaluate the other PSMs" help="(-subset-max-train) Recommended when analyzing huge numbers (>1 million) of PSMs. When set to 0, all PSMs are used for training as normal"/> <param name="param_cpos" type="float" value="0.0" label="Cpos, penalty for mistakes made on positive examples" help="(-cpos) Set by cross validation if not specified"/> <param name="param_cneg" type="float" value="0.0" label="Cneg, penalty for mistakes made on negative examples" help="(-cneg) Set by cross validation if not specified"/> <param name="param_testFDR" type="float" value="0.01" label="False discovery rate threshold for evaluating best cross validation result and the reported end result" help="(-testFDR) "/> <param name="param_trainFDR" type="float" value="0.01" label="False discovery rate threshold to define positive examples in training" help="(-trainFDR) Set to testFDR if 0"/> <param name="param_maxiter" type="integer" value="10" label="Maximal number of iterations" help="(-maxiter) "/> <param name="param_quick_validation" display="radio" type="boolean" truevalue="-quick-validation" falsevalue="" checked="false" optional="True" label="Quicker execution by reduced internal cross-validation" help="(-quick-validation) "/> <param name="param_init_weights" type="data" format="txt" label="Read initial weights to the given file" help="(-init-weights) "/> <param name="param_default_direction" type="text" size="30" label="The most informative feature given as the feature name, can be negated to indicate that a lower value is bette" help="(-default-direction) "> <sanitizer> <valid initial="string.printable"> <remove value="'"/> <remove value="""/> </valid> </sanitizer> </param> <param name="param_verbose" type="integer" value="2" label="Set verbosity of output: 0=no processing info, 5=all" help="(-verbose) "/> <param name="param_unitnorm" display="radio" type="boolean" truevalue="-unitnorm" falsevalue="" checked="false" optional="True" label="Use unit normalization [0-1] instead of standard deviation normalization" help="(-unitnorm) "/> <param name="param_test_each_iteration" display="radio" type="boolean" truevalue="-test-each-iteration" falsevalue="" checked="false" optional="True" label="Measure performance on test set each iteration" help="(-test-each-iteration) "/> <param name="param_override" display="radio" type="boolean" truevalue="-override" falsevalue="" checked="false" optional="True" label="Override error check and do not fall back on default score vector in case of suspect score vecto" help="(-override) "/> <param name="param_seed" type="integer" value="1" label="Setting seed of the random number generato" help="(-seed) "/> <param name="param_doc" type="integer" value="0" label="Include description of correct features" help="(-doc) "/> <param name="param_klammer" display="radio" type="boolean" truevalue="-klammer" falsevalue="" checked="false" optional="True" label="Retention time features calculated as in Klammer et al" help="(-klammer) Only available if -doc is set"/> <param name="param_fasta" type="data" format="fasta" optional="True" label="Provide the fasta file as the argument to this flag, which will be used for protein grouping based on an in-silico digest (only valid if option -protein-level-fdrs is active)" help="(-fasta) "/> <param name="param_decoy_pattern" type="text" size="30" value="random" label="Define the text pattern to identify the decoy proteins and/or PSMs, set this up if the label that identifies the decoys in the database is not the default (Only valid if option -protein-level-fdrs is active)" help="(-decoy-pattern) "> <sanitizer> <valid initial="string.printable"> <remove value="'"/> <remove value="""/> </valid> </sanitizer> </param> <param name="param_post_processing_tdc" display="radio" type="boolean" truevalue="-post-processing-tdc" falsevalue="" checked="false" optional="True" label="Use target-decoy competition to assign q-values and PEPs" help="(-post-processing-tdc) "/> <param name="param_force" display="radio" type="boolean" truevalue="-force" falsevalue="" checked="false" optional="True" label="Overwrite tool specific checks" help="(-force) "/> </expand> </inputs> <outputs> <data name="param_out" format="idxml"/> <data name="param_mzid_out" format="mzid"/> <data name="param_weights" format="data"/> </outputs> <help>Facilitate input to Percolator and reintegrate. For more information, visit https://abibuilder.informatik.uni-tuebingen.de/archive/openms/Documentation/release/2.3.0/html/TOPP_PercolatorAdapter.html</help> </tool>