<tool id="EBGeneMultiCondTest" name="Gene level DE test across multiple conditions">
  <description>Runs EBSeq to find DE genes across multiple (more than two) conditions</description>
  <command>R --quiet --slave --file=$GALAXY_ROOT_DIR/tools/EBSeq/EBGeneMultiCondTest.R --args $Gene_Expression $First_Row_Sample_Names $Conditions $Patterns $PP_of_each_pattern $Pattern_with_highest_PP $Sizes</command>
  <inputs>
		<param name="Gene_Expression" type="data" format="tabular" label="Gene Expression (tab delimited, please use the unnormalized values, e.g. expected counts form RSEM)"/>
		<param name="First_Row_Sample_Names" type="select" format="text">
			<label>The First Row is Sample Names?</label>
			<option value="y">Yes</option>
			<option value="n">No</option>
			</param>
		<param name="Conditions" type="text" size="60" value="C1,C2" label="Enter which condition each
			sample belongs to (separated by comma, no space please)." 
			help=""/>
		<param name="Patterns" type="data" format="tabular" label="Patterns of Interests"/>
  </inputs>
  <outputs>
		<data format="tabular" name="PP_of_each_pattern" />
		<data format="tabular" name="Pattern_with_highest_PP" />
                <data format="tabular" name="Sizes" />
  </outputs>

  <help>
The input Conditions should have exactly two levels. The length of the Condition vector should be exactly the same as the number of columns in the data file (except the gene names column).

The patterns of interests could be obtained by function Get All Possible Patterns (and optionally, if there are too many patterns generated, the function Choose Patterns could be used to choose only subset of the patterns.)

Three output files will be generated. The first file contains the Posterior probability of being each pattern. The second file contains the pattern with highest PP for each gene and the normalized expressions. Genes are with the same order as in input file.
The last file provides the library size factor for each sample.


</help>


</tool>