annotate ipapy2_clustering.xml @ 0:cb18b8fcb441 draft default tip

planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/ipapy2 commit 64b61ff2823b4f54868c0ab7a4c0dc49eaf2979a

<tool id="ipapy2_clustering" name="ipaPy2 clustering" version="@TOOL_VERSION@+galaxy0" profile="@PROFILE@">
    <description>clustering MS1 features based on correlation across samples as preparation for ipaPy2</description>
    <macros>
        <import>macros.xml</import>
    </macros>
    <expand macro="requirements"/>
    <command detect_errors="exit_code"><![CDATA[
        python3 '${__tool_directory__}/ipapy2_clustering.py'
        --input_dataset '${unclustered_MS1_intensities}' '${unclustered_MS1_intensities.ext}'
        --Cthr ${Cthr}
        --RTwin ${RTwin}
        --Intmode ${Intmode}
        --output_dataset '${clustered_MS1_intensities}' '${clustered_MS1_intensities.ext}'

    ]]></command>
    <inputs>
        <param label="Unclustered data" name="unclustered_MS1_intensities" type="data" format="csv,tsv,tabular,parquet" help="a csv file containing the measured intensities across several samples, yet to be clustered"/>
        <section name="clustering" title="clustering settings" expanded="true">
            <param name="Cthr" type="float" value="0.8" min="0" max="1">
                <label>correlation threshold</label>
                <help>Minimum correlation allowed in each cluster. Default value 0.8.</help>
            </param>
            <param name="RTwin" type="float" value="1" min="0">
                <label>RT threshold</label>
                <help>Maximum difference in RT time between features in the same cluster. Default value 1.</help>
            </param>
            <param name="Intmode" type="select">
                <label>intensity mode</label>
                <help>intensity mode. Default 'max' or 'ave'.</help>
                <option value="max" selected="true">max</option>
                <option value="ave">ave</option>
            </param>
        </section>
    </inputs>
    <outputs>
        <data label="${tool.name} on ${on_string}" name="clustered_MS1_intensities" format_source="unclustered_MS1_intensities" />
    </outputs>
    <tests>
        <test>
            <param name="unclustered_MS1_intensities" value="unclustered_MS1_intensities.csv"/>
            <output name="clustered_MS1_intensities" file="clustered_MS1_intensities.csv"/>
        </test>
    </tests>
    <help><![CDATA[
    Before using the ipaPy2 package, the processed data coming from an untargeted metabolomics experiment must be properly prepared.
    The data must be organized in a pandas dataframe containing the following columns:

    - **ids**: an unique numeric id for each mass spectrometry feature 
    - **mzs**: mass-to-charge ratios, usually the average across different samples.
    - **RTs**: retention times in seconds, usually the average across different samples.
    - **Int**: representative (e.g., maximum or average) intensity detected for each feature across samples (either peak area or peak intensity)

    The clustering of the features is a necessary and must be performed before running the IPA method.
    For this step, the use of widely used data processing software such as mzMatch and CAMERA is recommended.
    Nevertheless, the ipaPy2 library provides a function (clusterFeatures()) able to perform such step,
    starting from a dataframe containing the measured intensities across several samples (at least 3 samples, the more samples the better).
    Such dataframe should be organized as follows:

    +----+------+-----+-------------+-------------+-------------+
    | id | mz   | rt  | intensity_1 | intensity_2 | intensity_3 |
    +====+======+=====+=============+=============+=============+
    | 1  | 100  | 10  | 500         | 600         | 700         |
    +----+------+-----+-------------+-------------+-------------+
    | 2  | 200  | 20  | 800         | 900         | 1000        |
    +----+------+-----+-------------+-------------+-------------+
    | 3  | 300  | 30  | 1100        | 1200        | 1300        |
    +----+------+-----+-------------+-------------+-------------+
    ]]></help>
    <expand macro="citations"/>
</tool>