comparison geneBody_coverage2.xml @ 49:6b33e31bda10 draft

Uploaded tar based on https://github.com/lparsons/galaxy_tools/tree/master/tools/rseqc 1a3c419bc0ded7c40cb2bc3e7c87bfb01ddfeba2

48:2e6190c29c54

<tool id="rseqc_geneBody_coverage2" name="Gene Body Converage (Bigwig)" version="2.4">
    <description>
        Read coverage over gene body
    </description>
    <requirements>
        <requirement type="package" version="3.0.3">R</requirement>
        <requirement type="package" version="1.7.1">numpy</requirement>
        <requirement type="package" version="2.4">rseqc</requirement>
    </requirements>
    <command>
        geneBody_coverage2.py -i $input -r $refgene -o output
    </command>
    <stdio>
        <exit_code range="1:" level="fatal" description="An error occured during execution, see stderr and stdout for more information" />
        <regex match="[Ee]rror" source="both" description="An error occured during execution, see stderr and stdout for more information" />
    </stdio>
    <inputs>
        <param name="input" type="data" label="Input bigwig file" format="bigwig" />
        <param name="refgene" type="data" label="Reference Genome" format="bed" />
    </inputs>
    <outputs>
        <data name="outputpdf" format="pdf" from_work_dir="output.geneBodyCoverage.pdf" label="${tool.name} on ${on_string} (PDF)" />
        <data name="outputr" format="txt" from_work_dir="output.geneBodyCoverage_plot.r" label="${tool.name} on ${on_string} (R Script)" />
        <data name="outputtxt" format="txt" from_work_dir="output.geneBodyCoverage.txt" label="${tool.name} on ${on_string} (Text)" />
    </outputs>
    <help>
geneBody_coverage2.py
+++++++++++++++++++++

Similar to geneBody_coverage.py. This module takes bigwig instead of BAM as input, and thus
requires much less memory. The BigWig file could be arbitrarily large.

Example output:
    .. image:: http://dldcc-web.brc.bcm.edu/lilab/liguow/RSeQC/figure/geneBody_coverage.png
        :height: 600 px
        :width: 600 px
        :scale: 80 %    

-----

About RSeQC 
+++++++++++

The RSeQC_ package provides a number of useful modules that can comprehensively evaluate high throughput sequence data especially RNA-seq data. "Basic modules" quickly inspect sequence quality, nucleotide composition bias, PCR bias and GC bias, while "RNA-seq specific modules" investigate sequencing saturation status of both splicing junction detection and expression estimation, mapped reads clipping profile, mapped reads distribution, coverage uniformity over gene body, reproducibility, strand specificity and splice junction annotation.

The RSeQC package is licensed under the GNU GPL v3 license.

.. image:: http://rseqc.sourceforge.net/_static/logo.png

.. _RSeQC: http://rseqc.sourceforge.net/



    </help>
</tool>

49:6b33e31bda10

<tool id="rseqc_geneBody_coverage2" name="Gene Body Converage (Bigwig)" version="2.4galaxy1">
    <description>
        Read coverage over gene body
    </description>

    <macros>
        <import>rseqc_macros.xml</import>
    </macros>

    <requirements>
        <expand macro="requirement_package_r" />
        <expand macro="requirement_package_numpy" />
        <expand macro="requirement_package_rseqc" />
    </requirements>

    <expand macro="stdio" />

    <version_command><![CDATA[geneBody_coverage2.py --version]]></version_command>

    <command><![CDATA[
        geneBody_coverage2.py -i $input -r $refgene -o output
        ]]>
    </command>

    <inputs>
        <param name="input" type="data" label="Input bigwig file" format="bigwig" />
        <param name="refgene" type="data" label="Reference Genome" format="bed" />
    </inputs>

    <outputs>
        <data name="outputpdf" format="pdf" from_work_dir="output.geneBodyCoverage.pdf" label="${tool.name} on ${on_string} (PDF)" />
        <data name="outputr" format="txt" from_work_dir="output.geneBodyCoverage_plot.r" label="${tool.name} on ${on_string} (R Script)" />
        <data name="outputtxt" format="txt" from_work_dir="output.geneBodyCoverage.txt" label="${tool.name} on ${on_string} (Text)" />
    </outputs>

    <!-- Unable to succefully run this script, it seems deprecated and should probably be dropped
    <tests>
        <test>
            <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bigwig"/>
            <param name="refgene" value="hg19_RefSeq_chr1_1-100000.bed"/>
            <output name="outputcurvespdf" file="output.geneBodyCoverage.curves.pdf"/>
            <output name="outputr" file="output.geneBodyCoverage.r"/>
            <output name="outputtxt" file="output.geneBodyCoverage.txt"/>
        </test>
    </tests>
    -->

    <help><![CDATA[
geneBody_coverage2.py
+++++++++++++++++++++

Similar to geneBody_coverage.py. This module takes bigwig instead of BAM as input, and thus
requires much less memory. The BigWig file could be arbitrarily large.

Example output:
    .. image:: http://dldcc-web.brc.bcm.edu/lilab/liguow/RSeQC/figure/geneBody_coverage.png
        :height: 600 px
        :width: 600 px
        :scale: 80 %

-----

About RSeQC
+++++++++++

The RSeQC_ package provides a number of useful modules that can comprehensively evaluate high throughput sequence data especially RNA-seq data. "Basic modules" quickly inspect sequence quality, nucleotide composition bias, PCR bias and GC bias, while "RNA-seq specific modules" investigate sequencing saturation status of both splicing junction detection and expression estimation, mapped reads clipping profile, mapped reads distribution, coverage uniformity over gene body, reproducibility, strand specificity and splice junction annotation.

The RSeQC package is licensed under the GNU GPL v3 license.

.. image:: http://rseqc.sourceforge.net/_static/logo.png

.. _RSeQC: http://rseqc.sourceforge.net/

]]>
    </help>

    <expand macro="citations" />

</tool>