<tool id="abims_anova" name="Anova" version="1.2.0">

    <description>N-way anova. With ou Without interactions</description>

    <requirements>
	<requirement type="package" version="1.1_4">r-batch</requirement>
	<requirement type="package" version="1.2">r-venn</requirement>
    </requirements>

    <stdio>
        <exit_code range="1:" level="fatal" />
    </stdio>

    <command>
Rscript $__tool_directory__/abims_anova.r file '$input' sampleinfo '$sampleinfo' varinfo '$varinfo' mode '$mode'
condition "c('$condition_1'
#for $i, $s in enumerate( $conditions )
,'${s.condition}'
#end for
)"
interaction $interaction
method $method
threshold $threshold
selection_method $selection_method
sep '$sep'
dec '$dec'
outputdatapvalue '$varMetaPValue'
outputdatasignif '$dataSignif'
    </command>

    <inputs>
        <param name="input" type="data" label="Data Matrix file" format="tabular" help="Matrix of numeric data with headers." />
        <param name="sampleinfo" type="data" label="Sample Metadata file" format="tabular" help="Tabular file with the data metadata : one sample per line and at least two columns : ids and one condition" />
        <param name="varinfo" type="data" label="Variable Metadata file" format="tabular" help="Tabular file with information about your tested variables. Only used to aggregate generated information." />

        <param name="mode" type="select" help="Perform the anova tests on column/row; for W4M 3-tables format, use 'row'." format="text" optional="true">
            <label>Mode</label>
            <option value="row" selected="True">row</option>
            <option value="column">column</option>
        </param>

        <param name="condition_1" type="text" label="Condition" value="" help="The column name of the condition. ex: hour or treatment" optional="false" />
        <repeat name="conditions" title="Conditions for N-ways anova">
            <param name="condition" type="text" label="Condition" value="" help="The column name of the condition. ex: hour or treatment" />
        </repeat>

        <param name="interaction" type="boolean" label="Enable interaction response p-values" truevalue="T" falsevalue="F" help="Used if more than 1 conditon. The anova will produse p-value according to the interaction between your condition (ex: condition1:conditions2, condition1:conditions3, condition2:conditions3 and condition1:condition2:conditions3)" />

        <param name="method" type="select" help="Method used to apply a correction on the pvalue because of the number of test" >
            <label>PValue adjusted method</label>
            <option value="BH">BH</option>
            <option value="holm">holm</option>
            <option value="bonferroni">bonferroni</option>
            <option value="hochberg">hochberg</option>
            <option value="hommel">hommel</option>
            <option value="BY">BY</option>
            <option value="fdr">fdr</option>
            <option value="none" selected="True">none</option>
        </param>

        <param name="threshold" type="float" label="Threshold" value="0.01" help="max adjusted p.value accepted" />

        <param name="selection_method" type="select" help="Intersection: all condition p-value must be under the threshold. Union: at least condition p-value must be under the threshold. ">
            <label>Selection method</label>
            <option value="intersection" selected="true">intersection / strong</option>
            <option value="union">union / weak</option>
        </param>

        <param name="sep" type="select" format="text">
            <label>Separator of columns</label>
            <option value="tabulation">tabulation</option>
            <option value="semicolon">;</option>
            <option value="comma">,</option>
        </param>

        <param name="dec" type="text" label="Decimal separator" value="." help="" />

    </inputs>

    <outputs>
        <data name="varMetaPValue" format_source="varinfo" label="${varinfo.name}_anova_pvalue.${varinfo.ext}"/>
        <data name="dataSignif" format="pdf" label="${input.name}_anova_signif"/>
    </outputs>

    <tests>
        <test>
            <param name="input" value="dataMatrix.tsv"/>
            <param name="sampleinfo" value="sampleMetadata.tsv"/>
            <param name="varinfo" value="variableMetadata.tsv"/>
            <param name="mode" value="row"/>
            <param name="condition_1" value="age"/>
            <param name="conditions_0|condition" value="gender"/>
            <param name="interaction" value="F"/>
            <param name="method" value="BH"/>
            <param name="threshold" value="0.05"/>
            <param name="selection_method" value="union"/>
            <param name="sep" value="tabulation"/>
            <param name="dev" value="."/>
            <output name="varMetaPValue" file="variableMetadata.tsv_anova_pvalue.tabular" />
            <output name="dataSignif" file="dataMatrix.tsv_anova_signif.pdf" compare="sim_size" delta="600" />
        </test>
    </tests>

    <help>

.. class:: infomark

**Authors** Gildas Le Corguille  ABiMS - UPMC/CNRS - Station Biologique de Roscoff - gildas.lecorguille|at|sb-roscoff.fr
Melanie Petera - PFEM ; INRA ; MetaboHUB

---------------------------------------------------

=====
Anova
=====

-----------
Description
-----------

Analysis of variance (ANOVA) is used to analyze the differences between group means and their associated procedures,
in which the observed variance in a particular variable is partitioned into components attributable to different sources of variation.



-----------
Input files
-----------

+----------------------------+------------+
| Parameter : num + label    |   Format   |
+============================+============+
| 1 : Data Matrix file       | Tabular    |
+----------------------------+------------+
| 2 : Sample Metadata file   | Tabular    |
+----------------------------+------------+
| 3 : Variable Metadata file | Tabular    |
+----------------------------+------------+


------------
Output files
------------



***.anova_pvalue.tabular**

    | Your variable metadata file completed with columns of p-values, result of selection method and means of subgroups.

***.anova_signif.pdf**

    | A pdf file containing a Venn diagram and boxplots of significant variables.


------

.. class:: infomark

The outputs ***.anova_filtered.tabular** is a tabular file. You can continue your analysis using it in the following tools:

    | Generic_filter
    | Hierarchical Clustering



---------------------------------------------------



    </help>

    <citations>
        <citation type="bibtex">@ARTICLE{fisher,
           author = {Ronald A. Fisher},
           title = {The Correlation between Relatives on the Supposition of Mendelian Inheritance},
           journal = {Philosophical Transactions of the Royal Society of Edinburgh},
           year = {1918},
           volume = {52},
           pages = {399-433}
        }</citation>
    </citations>

</tool>