annotate kruskal_wallis.xml @ 1:2e7d47c0b027 draft

"planemo upload for repository https://[e-mail]/repos/malex/secimtools"

<tool id="secimtools_kruskal_wallis" name="Kruskal-Wallis Non-Parametric Test" version="@WRAPPER_VERSION@">
    <description>on features (rows).</description>
    <macros>
        <import>macros.xml</import>
    </macros>
    <expand macro="requirements" />
    <command detect_errors="exit_code"><![CDATA[
kruskal_wallis.py
--input $input
--design $design
--uniqueID $uniqueID
--group $group
--summaries $summaries
--flags $flags
--volcano $volcano
    ]]></command>
    <inputs>
        <param name="input" type="data" format="tabular" label="Wide Dataset" help="Input your tab-separated wide format dataset. If file is not tab separated see TIP below."/>
        <param name="design" type="data" format="tabular" label="Design File" help="Input your design file (tab-separated). Note you need a 'sampleID' column. If not tab separated see TIP below."/>
        <param name="uniqueID" type="text" size="30" value="" label="Unique Feature ID" help="Name of the column in your wide dataset that has unique identifiers."/>
        <param name="group" type="text" size="30" label="Group/Treatment" help="Name of the column in your design file that contains group classifications."/>
    </inputs>
    <outputs>
        <data format="tabular" name="summaries" label="${tool.name} on ${on_string}: Summaries that include p-values and mean differences."/>
        <data format="tabular" name="flags" label="${tool.name} on ${on_string}: Flags that include 0.01,  0.05 and  0.10 significance levels for the pairwise differences. "/>
        <data format="pdf" name="volcano" label="${tool.name} on ${on_string}: Volcano plots for the pairwise differences."/>
    </outputs>
    <tests>
        <test>
            <param name="input"    value="ST000006_data.tsv"/>
            <param name="design"   value="ST000006_design.tsv"/>
            <param name="uniqueID" value="Retention_Index" />
            <param name="group"    value="White_wine_type_and_source" />
            <output name="summaries" file="ST000006_kruskal_wallis_with_group_summary.tsv" />
            <output name="flags"     file="ST000006_kruskal_wallis_with_group_flags.tsv" />
            <output name="volcano"   file="ST000006_kruskal_wallis_with_group_volcano.pdf" compare="sim_size" delta="10000" />
        </test>
    </tests>
    <help><![CDATA[

@TIP_AND_WARNING@

**Tool Description**

The tool performs Kruskal-Wallis non-parametric test, an analog of the one-way ANOVA F-test that does not rely on the normality assumption of the distribution.
Unlike t-tests or an ANOVA F-test, a Kruskal-Wallis test is based on ranks where ranks are compared between groups.
The test is performed (1) for samples from all groups together and (2) for the samples belonging to each group.
The user is referred to the literature for more details on the Kruskal-Wallis test and the computation/approximation of corresponding p-values.

Kruskal, William H., and W. Allen Wallis. "Use of ranks in one-criterion variance analysis." Journal of the American statistical Association 47, no. 260 (1952): 583-621.

Meyer, J. Patrick, and Michael A. Seaman. "A comparison of the exact Kruskal-Wallis distribution to asymptotic approximations for all sample sizes up to 105." The Journal of Experimental Education 81, no. 2 (2013): 139-156.

--------------------------------------------------------------------------------

**Input**

    - Two input datasets are required.


@WIDE@

**NOTE:** The sample IDs must match the sample IDs in the Design File
(below). Extra columns will automatically be ignored.

@METADATA@

@UNIQID@

**Group/Treatment**

        - Name of the column the Design File that contain group classifications.

--------------------------------------------------------------------------------

**Output**

Three different outputs are generated:

(1) a TSV file with the results, including p-values for each test and the corresponding differences between the means for comparisons between the groups.
(2) a TSV file containing indicator flags.  A flag = 1 if the difference between the groups is statistically significant.
(3) a PDF file with volcano plots for visual inspection of the differences between the treatment groups. The red dashed line in the volcano plot(s) corresponds to a 0.01 cutoff for p-values (2 on the negative log base 10 scale).

    ]]></help>
    <expand macro="citations"/>
</tool>