comparison tools/oncodrivefm_tool/oncodrivefm_tool.xml @ 0:8447ba178b06

Init

0:8447ba178b06

<tool id="oncodrivefm_tool" name="OncodriveFM">
    <description>OncodriveFM </description>
    <tool_dependency>
        <package name="oncodrivefm">
            <install version="0.6-dev">
                <actions>
                    <action type="setup_virtualenv">distribute</action>
                    <action type="setup_virtualenv">python-dateutil==2.1</action>
                    <action type="setup_virtualenv">pytz==2013b</action>
                    <action type="setup_virtualenv">numpy==1.7.1</action>
                    <action type="setup_virtualenv">scipy==0.12.0</action>
                    <action type="setup_virtualenv">pandas==0.12.0</action>
                    <action type="setup_virtualenv">statsmodels==0.4.3</action>
                    <action type="setup_virtualenv">https://bitbucket.org/bbglab/oncodrivefm/get/master.tar.gz</action>
                </actions>
            </install>
            <readme>OncodriveFm avalable at https://bitbucket.org/bbglab/oncodrivefm/</readme>
        </package>
    </tool_dependency>

    <command interpreter="python">
        #if $mappingpathcondition.hasmapfile=="yes"
            oncodrivefm_tool.py -N $samplings -e $estimator --gt $gene_threshold --pt $pathway_threshold -s $slices -m $mapping_path -o1 $output1 -o2 $output2 -i $input
        #else
            oncodrivefm_tool.py -N $samplings -e $estimator --gt $gene_threshold --pt $pathway_threshold -s $slices -o1 $output1 -o2 $output2 -i $input
        #end if
    </command>
    <inputs>
        <param name="input" format="tabular" type="data" label="Input" />
        <param name="samplings" type="integer" label="Samplings" help="Number of samplings to compute the FM bias pvalue" optional="true" value="10000"/>

        <param name="estimator" type="select" label="Estimator" help="Test estimator for computation" optional="true">
            <option value="median">Median</option>
            <option value="mean">Mean</option>
        </param>


        <param name="gene_threshold" type="integer" label="Gene Threshold" help="Minimum number of mutations per gene to compute the FM bias" optional="true" value="2"/>
        <param name="pathway_threshold" type="integer" label="Pathway Threshold" help="Minimum number of mutations per pathway to compute the FM bias" optional="true" value="10" />
        <param name="slices" type="text" label="Slices" help="Slices to process separated by commas(slices=SIFT,PPH2,MA)" optional="true" value="SIFT,PPH2,MA"/>
        <conditional name="mappingpathcondition">
            <param name="hasmapfile" type="select" label="Have a mapping gene file">
                <option value="no">No</option>
                <option value="yes">Yes</option>
            </param>
            <when value="yes">
                <param name="mapping_path" type="data" format="tabular" label=" File with mappings between genes and pathways to be analysed"/>
            </when>
        </conditional>
    </inputs>
    <outputs>

        <data format="tabular" name="output1"/>
        <data format="tabular" name="output2" >
            <filter>mappingpathcondition["hasmapfile"]=="yes"</filter>
        </data>
    </outputs>
    <help>
        **What it does**
        Oncodrive-fm is an approach to uncover driver genes or gene modules.
        It computes a metric of functional impact using three well-known methods (SIFT, PolyPhen2 and MutationAssessor)
        and assesses how the functional impact of variants found in a gene across several tumor samples deviates from
        a null distribution. It is thus based on the assumption that any bias towards the accumulation of variants
        with high functional impact is an indication of positive selection and can thus be used to detect candidate
        driver genes or gene modules.

         **Citation**
         If you use this Galaxy tool in work leading to a scientific publication please cite:

         Gonzalez-Perez A and Lopez-Bigas N. 2012. Functional impact bias reveals cancer drivers. Nucleic Acids Res., 10.1093/nar/gks743.

</tool>