interactivetool_rstudio_metabolomics-dataprocessing.xml

<tool id="interactive_tool_rstudio_metabolomics-dataprocessing" tool_type="interactive" name="RStudio MetabolomicsDataprocessing" version="0.1">
    <requirements>
        <container type="docker">hub.docker.com/repository/docker/yguitton/docker-galaxy-rstudio-metabolomics-dataprocessing:latest</container>
    </requirements>
    <entry_points>
        <entry_point name="RStudio" requires_domain="True">
            <port>80</port>
            <url>rstudio/</url>
        </entry_point>
    </entry_points>
    <environment_variables>
        <environment_variable name="HISTORY_ID" strip="True">${__app__.security.encode_id($jupyter_notebook.history_id)}</environment_variable> <!-- FIXME: Warning: The use of __app__ is deprecated and will break backward compatibility in the near future -->
        <environment_variable name="REMOTE_HOST">${__app__.config.galaxy_infrastructure_url}</environment_variable> <!-- FIXME: Warning: The use of __app__ is deprecated and will break backward compatibility in the near future -->
        <environment_variable name="GALAXY_WEB_PORT">8080</environment_variable>
        <environment_variable name="GALAXY_URL">$__galaxy_url__</environment_variable>
        <environment_variable name="DEBUG">true</environment_variable>
        <environment_variable name="DISABLE_AUTH">true</environment_variable>
        <environment_variable name="API_KEY" inject="api_key" />
    </environment_variables>
    <command detect_errors="aggressive"><![CDATA[
        #import re
        export GALAXY_WORKING_DIR=`pwd` &&
        mkdir -p ./rstudio/outputs/ &&
        mkdir -p ./rstudio/data &&

        ## change into the directory where the notebooks are located
        cd ./rstudio/ &&

        sed -i 's|/monitor.*||g' /etc/services.d/nginx/run &&

        /etc/init.d/syslog-ng start &&
        /init &
        ##rstudio-server start &&
        sleep 5 &&

        chmod 777 /tmp -R &&
        tail -f /var/log/rstudio-server/rserver.log

    ]]>
    </command>
    <inputs>
        <!--<param name="input" type="data" optional="true" label="Include data into the environment"/>-->
    </inputs>
    <outputs>
        <data name="jupyter_notebook" format="ipynb" label=""></data>
    </outputs>
    <tests>
        <test expect_num_outputs="1">
            <param name="mode" value="previous" />
            <param name="ipynb" value="test.ipynb" />
            <param name="run_it" value="true" />
            <output name="jupyter_notebook" file="test.ipynb" ftype="ipynb"/>
        </test>
    </tests>
    <help>
    This familiar R analysis software suite will let you explore your
    datasets in depth. Comes with ggplot2, RODBC, maps, shinyapps, knitr,
    LaTeX, bioconductor, cummeRbund, tidyverse, tidymodels, targets, 
    mixOmics, iClusterPlus, MOFA2 and many more pre-installed packages.
	For this Metabolomics Data Processing instance many packages have 
	been added from R for Massspectrometry.

    Galaxy offers you to use RStudio directly in Galaxy accessing and interacting with Galaxy datasets as you like. A very common use-case is to
    do the heavy lifting and data reduction steps in Galaxy and the plotting and more `interactive` part on smaller datasets in RStudio.

    The convenience functions gx_put() and gx_get() are available to you to interact with your current Galaxy history. You can save your workspace with gx_save().

    For example, gx_get(42) will fetch dataset 42 from your history and return the file location
    </help>
</tool>