<tool id="methylGSA" name="methylGSA" version="0.1.0" python_template_version="3.5">
    <description>Gene Set Analysis for DNA Methylation data</description>

    <requirements>
        <requirement type="package" version="0.6.0">bioconductor-IlluminaHumanMethylationEPICanno.ilm10b4.hg19</requirement>
        <requirement type="package" version="0.6.0">bioconductor-IlluminaHumanMethylation450kanno.ilmn12.hg19</requirement>
        <requirement type="package" version="1.8.0">bioconductor-methylGSA</requirement>
        <requirement type="package" version="1.20.3">r-getopt</requirement>
    </requirements>

    <command detect_errors="exit_code"><![CDATA[
        Rscript '$__tool_directory__/methylGSA.R' 
        --data_file '$data_file' 
        --test_method '$method' 
        --array_type '$array_type' 
        --group '$Group' 
        --GS_list '$geneset' 
        --minsize '$minSize'  
        --maxsize '$maxSize'  
        --result '$gsa_result'
        
    ]]></command>

    <inputs>
        <param name="data_file" type="data" format="txt" label="CpG IDs and their p-value" help="A text file with two columns: The CpG IDs and their p-values." />
        <param name="array_type" type="select" label="Array_type" help="450K or EPIC." >
            <option value="450K">450K</option>
            <option value="EPIC">EPIC</option>
        </param>
        <param name="Group" type="select" label="Group" help="See help for more details.">
            <option value="all">all</option>
            <option value="body">body</option>
            <option value="promoter1">promoter1</option>
            <option value="promoter2">promoter2</option>
        </param>
        <param name="method" type="select" label="Test method" display="radio" help="See help for more details." >
            <option value="methylglm">methylglm</option>
            <option value="gometh">gometh</option>
            <option value="RRA_ORA">RRA(ORA)</option>
            <option value="RRA_GSEA">RRA(GSEA)</option>
        </param>
        <param name="geneset" type="select" label="Gene sets" help="Select gene sets to test." >
            <option value="GO">Gene Ontology</option>
            <option value="KEGG">KEGG</option>
            <option value="Reactome">Reactome</option>
        </param> 
        
        <param name="minSize" type="integer" label="Minimum gene set size" value="15" min="1" max="1000" help="Gene sets with less than this number of elements will not be included in the analysis." />
        <param name="maxSize" type="integer" label="Maximum gene set size" value="500" min="1" max="1000" help="Gene sets with more than this number of elements will not be included in the analysis." />
        
    </inputs>

    <outputs>
        <data name="gsa_result" format="csv" label="methylGSA_result" />
    </outputs>

    <tests>
        <test>
            <param name="data_file" value="cpg.csv" ftype="txt" />
        <param name="array_type" value="450K"/>
        <param name="Group" value="all" />
        <param name="method" value="methylglm" />
        <param name="geneset" value="GO" />
        <param name="minSize" value="15" />
        <param name="maxSize" value="500" />
            <output name="gsa_result"  file="methylGSA_result.csv" ftype="csv" />    
        </test>
    </tests>

    <help><![CDATA[
                
    .. class:: infomark
    
    **What it does**
    
    **methylGSA** is a tool for gene set testing with length bias adjustment for DNA methylation data. 
    It allows users to identify enriched or over-represented gene sets or pathways from the Gene
    Ontology, KEGG and Reactome databases.

-------

=========
**Input**
=========
    
    **CpG IDs and their p-value**

    Users are expected to upload a txt file with two columns: The fist column with the CpG IDs, and the second column with the p-values correspond to the CpGs. For example:

    ===========   ===========
    cg13869341    0.307766
    cg14008030    0.257672
    cg12045430    0.552322
    cg20826792    0.056383
    cg00381604    0.468549
    cg20253340    0.483770
    cg21870274    0.812402
    ===========   ===========

    Files should be no more than 100MB. 
    
    **array_type**
    
    `450K`: Illumina 450 K Beadchip  
    
    `EPIC`: Illumina EPIC Beadchip
    
    **Group**
    
    **Group** defines the type of CpG to be considered by the `methylRRA` or `methylglm` functions. By default, 
    group is set to `all`, which means that all CpGs are considered regardless of their gene group. 
    If group is set to `body`, only CpGs on gene body will be considered. If group is `promoter1` 
    or `promoter2`, only CpGs on promoters will be considered. 
    Based on the annotation in IlluminaHumanMethylation450kanno.ilmn12.hg19 
    and IlluminaHumanMethylationEPICanno.ilm10b4.hg19, `body`, `promoter1` and `promoter2` are defined as:
    
        * body: CpGs whose gene group correspond to “Body” or “1stExon”
        * promoter1: CpGs whose gene group correspond to “TSS1500” or “TSS200”
        * promoter2: CpGs whose gene group correspond to “TSS1500”, “TSS200”, “1stExon”, or “5’UTR”
        
    **Test method**
    
        * methylglm: Implement logistic regression adjusting for number of probes in enrichment analysis
        * gometh: Gene ontology testing for Illumina methylation array data
        * RRA(ORA): Enrichment analysis with ORA method after adjusting multiple p-values of each gene by Robust Rank Aggregation
        * RRA(GSEA): Enrichment analysis with GSEA method after adjusting multiple p-values of each gene by Robust Rank Aggregation
    
    **Gene sets tested**
    
    * Gene Ontology: http://www.geneontology.org
    * KEGG (Kyoto Encyclopedia of Genes and Genomes): https://www.genome.jp/kegg/
    * Reactome: https://reactome.org
    
==========
**Output**
==========

    **methylGSA_result**
    This file is a csv file which contains gene set tests results.
    
    ]]></help>

    <citations>
        <citation type="doi">10.1093/bioinformatics/bty892</citation>    
    </citations>
    
</tool>