view withinvariation-26603602a823/mixomics_multilevel.xml @ 0:5086ad0c0992 draft default tip

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<tool id="mixomics_multilevel" name="Multilevel" version="0.5.0">

   <description>Data transformation: Within matrix decomposition for repeated measurements (cross-over design) with mixOmics package</description>
    
    <requirements>
        <requirement type="package" version="6.1.1">r-mixomics</requirement>
	    <requirement type="package" version="1.1_4">r-batch</requirement>
	    <requirement type="package" version="1.64.0">bioconductor-pcamethods</requirement>
    </requirements>
    
    <stdio>
        <exit_code range="1:" level="fatal" />
    </stdio>
	
  
  <command>
	  Rscript $__tool_directory__/mixomics_multilevel.r
	  
	  dataMatrix_in "$dataMatrix_in"
	  sampleMetadata_in "$sampleMetadata_in"
	  repmeasure "$repmeasure"
	  #if $transformation.option_transformation == "false"
		transfo "none"
	  #end if
	  #if $nblevel.option_level == "onelevel"
	   respL "$nblevel.respL"
	   respL2 "NULL"
	  #end if
	  #if $nblevel.option_level == "twolevel"
	   respL1 "$nblevel.respL1"
	   respL2 "$nblevel.respL2"
	  #end if
	  #if $transformation.option_transformation == "true"
	   transfo "go"
	   trans "$transformation.trans"
	   scale "$transformation.scale"
	   center "$transformation.center"
	  #end if
	  
  </command>
  <inputs>
    <param name="dataMatrix_in" label="Data matrix file" type="data" format="tabular" help="variable x sample, decimal: '.', missing: NA, mode: numerical, sep: tabular" />
    <param name="sampleMetadata_in" label="Sample metadata file" type="data" format="tabular" help="sample x metadata, decimal: '.', missing: NA, mode: character and numerical, sep: tabular" />
   	<param name="repmeasure" label="Repeated mesurement label (Individual IDs, ...)" type="text" value="none" help="Indicate the column name of the sample table to be used as repeated mesurement factor" />
    
	
    <conditional name="nblevel">
      <param name="option_level" type="select" label="Select number of levels1">
        <option value="onelevel" selected="True">One Level</option>
        <option value="twolevel">Two levels</option>
      </param>
      <when value="onelevel">
         <param name="respL" label="Level name (as in sampleMetadata)" type="text" value = "none" help="Indicate the column name of the sample table to be used as factor" />
      </when>
      <when value="twolevel">
		  <param name="respL1" label="First level name (as in sampleMetadata)" type="text" value = "none" help="Indicate the column name of the sample table to be used as first factor" />
          <param name="respL2" label="Second level name (as in sampleMetadata)" type="text" value = "none" help="Indicate the column name of the sample table to be used as second factor" />
	  </when>
    </conditional>
	<conditional name="transformation">
      <param name="option_transformation" type="boolean" label="Add transformation to dataMatrix before withinVariation" />
          <when value="false">
          </when>
      <when value="true">
          <param name="trans" label="Transformation" type="select" help="" >
		     <option value="none">none</option>
		     <option value="log2">log2</option>
             <option value="log10">log10</option>
             <option value="sqrt">square root</option>
		  </param>	 
          <param name="scale" label="Scaling" type="select" help="" >
		     <option value="none">none</option>
		     <option value="pareto">pareto</option>
             <option value="vector">vector</option>
             <option value="uv">UV</option>
		  </param>
		  <param name="center" label="Centering" type="boolean" />
      </when>
    </conditional>
  
	  
  </inputs>

  <outputs>
    <data name="dataMatrix_out" format="tabular" from_work_dir="dataMatrix_out.tsv" label="dataMatrix_out.tsv"  ></data>
    <data name="multilevelRData" format="rdata" from_work_dir="multilevel.RData" label="multilevel.RData" />
    <data name="log" format="txt" from_work_dir="multilevel.log" label="multilevel.log.txt" />
  </outputs>
 
  <tests>
        <test>
            <param name="dataMatrix_in" value="dataMatrix.csv"  ftype="tabular" />
            <param name="sampleMetadata_in" value="sampleMetadata.csv" ftype="tabular" />
			<param name="repmeasure" value="Subject" />
            <param name="nblevel|option_level" value="onelevel" />
            <param name="respL" value="Occasion" />
            <output name="dataMatrix_out" file="dataMatrix_out.tsv" lines_diff="2" />
        </test>
	    <test>
            <param name="dataMatrix_in" value="dataMatrix.csv"  ftype="tabular" />
            <param name="sampleMetadata_in" value="sampleMetadata.csv" ftype="tabular" />
			<param name="repmeasure" value="Subject" />
            <param name="nblevel|option_level" value="onelevel" />
            <param name="respL" value="Occasion" />
			<param name="transformation|option_transformation" value="true" />
			<param name="transfo" value="go" />
			<param name="trans" value="log10" />
			<param name="scale" value="pareto" />
			<param name="center" value="false" />
            <output name="dataMatrix_out" file="dataMatrix_out_log10.tsv" lines_diff="2" />
        </test>
     
  </tests>
  

  <help>

.. class:: infomark

**Author(s)**  Benoit Liquet, Kim-Anh Le Cao, Benoit Gautier, Ignacio Gonzalez.

.. class:: infomark

**Galaxy wrapper and scripts developpers for W4M integration** Guitton Yann LABERCA [e-mail]

===========
Description
===========

withinVariation function decomposes the Within variation in the dataMatrix (One or two-factor analyses are available). The resulting  matrix is then input in any multivariate analyses.

withinVariation simply returns the Xw within matrix, which can be input in the other multivariate approaches already implemented in mixOmics 


That tool make use of withinVariation function for cross-over design experiment (Repeated mesurement) from mixOmics R package packurl_

.. _packurl: https://CRAN.R-project.org/package=mixOmics

For details information about mixOmics please connect to link_

.. _link: http://mixomics.org/

**Please cite:**
Kim-Anh Le Cao, Florian Rohart, Ignacio Gonzalez, Sebastien Dejean with key contributors Benoit Gautier, Francois Bartolo, 
contributions from Pierre Monget, Jeff Coquery, FangZou Yao and Benoit Liquet(2016). 
mixOmics: Omics Data Integration Project. R package version 6.1.1. 
 
  </help>
  
    <citations>
		<citation type="doi">10.1186/1471-2105-13-325</citation>
		<citation type="doi">10.1007/s11306-009-0185-z</citation>
        <citation type="doi">10.1093/bioinformatics/btu813</citation>
    </citations>
</tool>