annotate svm.xml @ 56:374c9a2bc1c2 draft

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<tool id="svm" name="svm" version="1.0.0">
  <description>predict phenotype using a SVM approach</description>
  <command interpreter="Rscript">
	  svm.R $config &gt; ${output1}
  </command>
  
  <inputs>
	<param name="genotype" type="data"
		label="genotype data" help="a tabular datatype containing the encoded genotypes" 
	/>
		  
	<param name="phenotype" type="data"
			label="phenotype data" help=" a tabular datatype containing the phenotypes " 
			/>
			
	<param name="kernel" type="text" value="radial"
			label="name of the kernel" help= " four possibilities : radial, linear, polynomial or sigmoid. Any other value is treated as radial" 
			/>		
	
	<param name="cost" type="float" value="-1"
			label="cost" help="the cost parameter of SVM used by all kernels. Suitable values are between 0.1 and 1000. -1 means the parameter must be optimized by the tool " 
			/>
			
	<param name="gamma" type="float" value="-1"
			label="gamma" help="the gamma parameter of SVM used by radial, polynomial and sigmoid kernels. Suitable values are between 1e-06 and 1. -1 means the parameter must be optimized by the tool " 
			/>
			
	<param name="coeficient" type="float" value="-1"
			label="coeficient" help="the coeficient parameter of SVM used by polynomial kernel. Suitable values are between 0 and 4. -1 means the parameter must be optimized by the tool " 
			/>
			
	<param name="degree" type="float" value="-1"
			label="degree" help="the maximum dgree of the polynomial kernel. Suitable values are between 1 and 3. -1 means the parameter must be optimized by the tool " 
			/>
	
	<param name="eval" type="integer" value="0"
			label="do evaluation" help=" whether to produce a model or to use folds to evaluate the tool. 1 means the tool will be evaluate (and a folds argument is required) any other value produces a model " 
	/>
	
	<param name="folds" type="data" optional="true"
			label="folds" help=" OPTIONAL ARGUMENT path to a folds file containing folds indexes in a R list called /folds/ such as produced by the folds tools in OGHMA suite. " 
			/>
		
	<param name="model" type="text"
			label="path to the output folds" help= " a path to a file where the results (depending on the chosen mode) will be writen" 
	/>
  </inputs>
  
  <configfiles>
    <configfile name="config">
## Desc: this file is sourced in encode wrapper script
##  as means to pass all galaxy params to R
"${genotype}" -> genotype
"${phenotype}" -> phenotype
"${eval}" -> doEvaluation
"${folds}" -> folds
"${model}" -> out
"${kernel}" -> kernel
"${gamma}" -> g
"${cost}" -> c
"${coeficient}" -> coef
"${degree}" -> d

    </configfile>
</configfiles>
  
<outputs>
	<data format="tabular" name = "output1" label="SVM output" />
</outputs>
  
  <help>
	  make the classification using the SVM method
  </help>
</tool>