<tool id="mlmm" name="MLMM" version="1.0">
	<description>GWAS using Multi-Locus Mixed-Model (MLMM)</description>
	<requirements>
		<requirement type="binary">Rscript</requirement>
	</requirements>
	<command interpreter="bash">./MLMM.sh $geno $map $pheno $steps $method $output $pdf $kinship $rss $step_table $log
    </command>
	<inputs>
		<param format="txt" name="geno" type="data" label="Genotype matrix" help="NxM, N = individuals in line, M = Markers in columns, Genotype coded in 0,1,2"/>
		<param type="data" format="txt" name="map" label="SNP Information file" help="3 columns: SNP, Chrom, Pos"/>
		<param format="txt" name="pheno" type="data" label="Phenotype matrix" help="NxT, N = individuals in line, T = Trait in columns (Phenot1, Phenot2...)"/>
		<param type="text" name="steps" label="Maximum number of steps for the forward approach" value="10"/>
		<param name="method" type="select">
                        <option value="extBIC">EBIC</option>
                        <option value="mbonf" selected="True">MBonf</option>
                </param>
	</inputs>
	<outputs>
		<data format="txt" name="output" label="Association results"/>
		<data format="txt" name="kinship" label="Kinship matrix"/>
		<data format="pdf" name="pdf" label="PDF Graphical outputs"/>
		<data format="txt" name="rss" label="RSS"/>
		<data format="txt" name="step_table" label="Step Table"/>
		<data format="txt" name="log" label="Log file"/>
	</outputs>
	<help>
	

.. class:: infomark

**Program encapsulated in Galaxy by Southgreen**

.. class:: infomark

**MLMM version 1.0**

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==============
 Please cite: 
==============

"An efficient multi-locus mixed-model approach for genome-wide association studies in structured populations.", **Segura V, Vilhjalmsson BJ, Platt A, Korte A, Seren U, Long Q, Nordborg M.**, Nature Genetics, 44: 825-830, 2012.

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===========
 Overview:
===========

MLMM is an efficient multi-locus mixed-model approach for genome-wide association studies in structured populations.

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For further informations, please visite the MLMM_ website.


.. _MLMM: https://sites.google.com/site/vincentosegura/mlmm
	</help>

</tool>