Mercurial > repos > galaxyp > openms_rtmodel
diff RTModel.xml @ 0:8480765683cf draft
planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/openms commit fb85d488133bb2b5f483b52b2db0ac66038fafb8
author | galaxyp |
---|---|
date | Wed, 01 Mar 2017 12:32:28 -0500 |
parents | |
children | b68f859bd5f3 |
line wrap: on
line diff
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/RTModel.xml Wed Mar 01 12:32:28 2017 -0500 @@ -0,0 +1,182 @@ +<?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 CTD2Galaxy.--> +<!--Proposed Tool Section: [Peptide property prediction]--> +<tool id="RTModel" name="RTModel" version="2.1.0"> + <description>Trains a model for the retention time prediction of peptides from a training set.</description> + <macros> + <token name="@EXECUTABLE@">RTModel</token> + <import>macros.xml</import> + </macros> + <expand macro="references"/> + <expand macro="stdio"/> + <expand macro="requirements"/> + <command>RTModel + +#if $param_in: + -in $param_in +#end if +#if $param_in_positive: + -in_positive $param_in_positive +#end if +#if $param_in_negative: + -in_negative $param_in_negative +#end if +#if $param_out: + -out $param_out +#end if +#if $param_svm_type: + -svm_type $param_svm_type +#end if +#if $param_nu: + -nu $param_nu +#end if +#if $param_p: + -p $param_p +#end if +#if $param_c: + -c $param_c +#end if +#if $param_kernel_type: + -kernel_type $param_kernel_type +#end if +#if $param_degree: + -degree $param_degree +#end if +#if $param_border_length: + -border_length $param_border_length +#end if +#if $param_max_std: + -max_std $param_max_std +#end if +#if $param_k_mer_length: + -k_mer_length $param_k_mer_length +#end if +#if $param_sigma: + -sigma $param_sigma +#end if +#if $param_total_gradient_time: + -total_gradient_time $param_total_gradient_time +#end if +#if $param_first_dim_rt: + -first_dim_rt +#end if +#if $param_additive_cv: + -additive_cv +#end if +#if $param_cv_skip_cv: + -cv:skip_cv +#end if +#if $param_cv_number_of_runs: + -cv:number_of_runs $param_cv_number_of_runs +#end if +#if $param_cv_number_of_partitions: + -cv:number_of_partitions $param_cv_number_of_partitions +#end if +#if $param_cv_degree_start: + -cv:degree_start $param_cv_degree_start +#end if +#if $param_cv_degree_step_size: + -cv:degree_step_size $param_cv_degree_step_size +#end if +#if $param_cv_degree_stop: + -cv:degree_stop $param_cv_degree_stop +#end if +#if $param_cv_p_start: + -cv:p_start $param_cv_p_start +#end if +#if $param_cv_p_step_size: + -cv:p_step_size $param_cv_p_step_size +#end if +#if $param_cv_p_stop: + -cv:p_stop $param_cv_p_stop +#end if +#if $param_cv_c_start: + -cv:c_start $param_cv_c_start +#end if +#if $param_cv_c_step_size: + -cv:c_step_size $param_cv_c_step_size +#end if +#if $param_cv_c_stop: + -cv:c_stop $param_cv_c_stop +#end if +#if $param_cv_nu_start: + -cv:nu_start $param_cv_nu_start +#end if +#if $param_cv_nu_step_size: + -cv:nu_step_size $param_cv_nu_step_size +#end if +#if $param_cv_nu_stop: + -cv:nu_stop $param_cv_nu_stop +#end if +#if $param_cv_sigma_start: + -cv:sigma_start $param_cv_sigma_start +#end if +#if $param_cv_sigma_step_size: + -cv:sigma_step_size $param_cv_sigma_step_size +#end if +#if $param_cv_sigma_stop: + -cv:sigma_stop $param_cv_sigma_stop +#end if +#if $adv_opts.adv_opts_selector=='advanced': + #if $adv_opts.param_force: + -force +#end if +#end if +</command> + <inputs> + <param name="param_in" type="data" format="txt,idxml" optional="True" label="This is the name of the input file (RT prediction)" help="(-in) It is assumed that the file type is idXML. Alternatively you can provide a .txt file having a sequence and the corresponding rt per line. <br>"/> + <param name="param_in_positive" type="data" format="idxml" optional="True" label="input file with positive examples (peptide separation prediction)" help="(-in_positive) "/> + <param name="param_in_negative" type="data" format="idxml" optional="True" label="input file with negative examples (peptide separation prediction)" help="(-in_negative) "/> + <param name="param_svm_type" display="radio" type="select" optional="False" value="NU_SVR" label="the type of the svm (NU_SVR or EPSILON_SVR for RT prediction, automatically set <br>to C_SVC for separation prediction)" help="(-svm_type) "> + <option value="NU_SVR" selected="true">NU_SVR</option> + <option value="NU_SVC">NU_SVC</option> + <option value="EPSILON_SVR">EPSILON_SVR</option> + <option value="C_SVC">C_SVC</option> + </param> + <param name="param_nu" type="float" min="0.0" max="1.0" optional="True" value="0.5" label="the nu parameter [0..1] of the svm (for nu-SVR)" help="(-nu) "/> + <param name="param_p" type="float" value="0.1" label="the epsilon parameter of the svm (for epsilon-SVR)" help="(-p) "/> + <param name="param_c" type="float" value="1.0" label="the penalty parameter of the svm" help="(-c) "/> + <param name="param_kernel_type" display="radio" type="select" optional="False" value="OLIGO" label="the kernel type of the svm" help="(-kernel_type) "> + <option value="LINEAR">LINEAR</option> + <option value="RBF">RBF</option> + <option value="POLY">POLY</option> + <option value="OLIGO" selected="true">OLIGO</option> + </param> + <param name="param_degree" type="integer" min="1" optional="True" value="1" label="the degree parameter of the kernel function of the svm (POLY kernel)" help="(-degree) "/> + <param name="param_border_length" type="integer" min="1" optional="True" value="22" label="length of the POBK" help="(-border_length) "/> + <param name="param_max_std" type="float" min="0.0" optional="True" value="10.0" label="max standard deviation for a peptide to be included (if there are several ones for one peptide string)(median is taken)" help="(-max_std) "/> + <param name="param_k_mer_length" type="integer" min="1" optional="True" value="1" label="k_mer length of the POBK" help="(-k_mer_length) "/> + <param name="param_sigma" type="float" value="5.0" label="sigma of the POBK" help="(-sigma) "/> + <param name="param_total_gradient_time" type="float" min="1e-05" optional="True" value="1.0" label="the time (in seconds) of the gradient (only for RT prediction)" help="(-total_gradient_time) "/> + <param name="param_first_dim_rt" display="radio" type="boolean" truevalue="-first_dim_rt" falsevalue="" checked="false" optional="True" label="if set the model will be built for first_dim_rt" help="(-first_dim_rt) "/> + <param name="param_additive_cv" display="radio" type="boolean" truevalue="-additive_cv" falsevalue="" checked="false" optional="True" label="if the step sizes should be interpreted additively (otherwise the actual value is multiplied <br>with the step size to get the new value" help="(-additive_cv) "/> + <param name="param_cv_skip_cv" display="radio" type="boolean" truevalue="-cv:skip_cv" falsevalue="" checked="false" optional="True" label="Set to enable Cross-Validation or set to true if the model should just be trained with 1 set of specified parameters" help="(-skip_cv) "/> + <param name="param_cv_number_of_runs" type="integer" min="1" optional="True" value="1" label="number of runs for the CV (each run creates a new random partition of the data)" help="(-number_of_runs) "/> + <param name="param_cv_number_of_partitions" type="integer" min="2" optional="True" value="10" label="number of CV partitions" help="(-number_of_partitions) "/> + <param name="param_cv_degree_start" type="integer" min="1" optional="True" value="1" label="starting point of degree" help="(-degree_start) "/> + <param name="param_cv_degree_step_size" type="integer" value="2" label="step size point of degree" help="(-degree_step_size) "/> + <param name="param_cv_degree_stop" type="integer" value="4" label="stopping point of degree" help="(-degree_stop) "/> + <param name="param_cv_p_start" type="float" value="1.0" label="starting point of p" help="(-p_start) "/> + <param name="param_cv_p_step_size" type="float" value="10.0" label="step size point of p" help="(-p_step_size) "/> + <param name="param_cv_p_stop" type="float" value="1000.0" label="stopping point of p" help="(-p_stop) "/> + <param name="param_cv_c_start" type="float" value="1.0" label="starting point of c" help="(-c_start) "/> + <param name="param_cv_c_step_size" type="float" value="10.0" label="step size of c" help="(-c_step_size) "/> + <param name="param_cv_c_stop" type="float" value="1000.0" label="stopping point of c" help="(-c_stop) "/> + <param name="param_cv_nu_start" type="float" min="0.0" max="1.0" optional="True" value="0.3" label="starting point of nu" help="(-nu_start) "/> + <param name="param_cv_nu_step_size" type="float" value="1.2" label="step size of nu" help="(-nu_step_size) "/> + <param name="param_cv_nu_stop" type="float" min="0.0" max="1.0" optional="True" value="0.7" label="stopping point of nu" help="(-nu_stop) "/> + <param name="param_cv_sigma_start" type="float" value="1.0" label="starting point of sigma" help="(-sigma_start) "/> + <param name="param_cv_sigma_step_size" type="float" value="1.3" label="step size of sigma" help="(-sigma_step_size) "/> + <param name="param_cv_sigma_stop" type="float" value="15.0" label="stopping point of sigma" help="(-sigma_stop) "/> + <expand macro="advanced_options"> + <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="txt"/> + </outputs> + <help>Trains a model for the retention time prediction of peptides from a training set. + + +For more information, visit http://ftp.mi.fu-berlin.de/OpenMS/release-documentation/html/TOPP_RTModel.html</help> +</tool>