annotate viscorvar_matcoraddvar.xml @ 4:d4e9f7546dfa draft

"planemo upload for repository https://gitlab.com/bilille/galaxy-viscorvar commit 579dc54316e8ede493f86f434a87d3d7b692b023"

<tool id="viscorvar_matcoraddvar" name="visCorVar matCorAddVar" version="@TOOL_VERSION@+galaxy0" profile="16.04" workflow_compatible="true">

    <description>determine the correlation circles that can be overlaid and compute the correlations</description>

    <macros>
        <import>macros.xml</import>
        <import>macros_viscorvar.xml</import>
    </macros>

    <expand macro="requirements"/>
    <expand macro="stdio"/>

    <command detect_errors="aggressive"><![CDATA[

        @COMMAND_RSCRIPT@/viscorvar_matcoraddvar.R

        --input_rdata ${input_rdata}
        --block_Y_file ${block_Y}

        ##--cutoff_comp ${cutoff_comp}
        --cutoff_comp 0.75
        #if str($var_of_interest_file) !='':
            --interest_var_file ${var_of_interest_file}
        #end if

        --output_rdata ${output_rdata}
        --output_response_var ${output_response_var}
        --output_blocks_comb ${output_blocks_comb}

        @COMMAND_LOG_EXIT@

    ]]></command>

    <inputs>
        <param name="input_rdata" type="data" format="rdata"
               label="Input RData file from block.SPLSDA"
               help="this is the RData output file from the block.splsda function" />
        <param name="block_Y" type="data" format="tabular"
               label="Block Y"
               help="Block Y is a table. A column determines which sample is associated with a phenotype (value equals to 1) or not (value equals to 0). For the file structure, see below in the section Input files" />
        <!-- Fichier avec noms de gènes/variables, donné par l'utilisateur -->
        <param name="var_of_interest_file" type="data" format="txt" optional="true"
               label="Variables of interest (Optional)"
               help="variables not belonging to any block will not be considered. For the file structure, see below in the section Input files"/>
        <!-- <param name="cutoff_comp" type="float" value="0.775" min="0" max="1"
               label="Cutoff comp"
               help="[cutoff_comp] Two correlation circles will be superimposed if the correlation of their first and second axis is greater than cutoff_comp in absolute value." /> -->
    </inputs>

    <outputs>
        <data name="output_rdata" format="rdata" label="${tool.name}_output.RData" />
        <data name="output_response_var" format="tabular" label="${tool.name}_response_var.tsv" />
        <data name="output_blocks_comb" format="tabular" label="${tool.name}_blocks_comb.tsv" />
    </outputs>

    <tests>
    </tests>

    <help><![CDATA[

@HELP_AUTHORS@

======================
visCorVar matCorAddVar
======================

-----------
Description
-----------

This tool is a pre-processing step of the pipeline. It computes the correlations
between omics datasets variables, variables of interest (optional), response variables and
the components which are output of the data integration. The variables of interest are omics
datasets variables that will be added to the network. It also determines the omics datasets
for which the correlated variables of these omics datasets can be visualized with correlation
circles and networks.

-----------------
Workflow position
-----------------

**Upstream tools**

======================= =================================== ========
Name                    Output file                         Format
======================= =================================== ========
mixOmics.block.splsda   mixomics_blocksplsda_output.RData   rdata
======================= =================================== ========

**Downstream tools**

================================ ========================================= ========
Name                             Output file                               Format
================================ ========================================= ========
visCorVar.circleCor              viscorvar_matcoraddvar_output.RData       rdata
-------------------------------- ----------------------------------------- --------
visCorVar.computeMatSimilarity   viscorvar_matcoraddvar_output.RData       rdata
-------------------------------- ----------------------------------------- --------
visCorVar.networkVar             viscorvar_matcoraddvar_response_var.tsv   tabular
================================ ========================================= ========

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

-----------
Input files
-----------

+-----------------------------------------+-----------+
| Parameter : num + label                 |  Format   |
+=========================================+===========+
| 1 : Rdata mixOmics.block.splsda output  |  Rdata    |
+-----------------------------------------+-----------+
| 2 : Block Y                             |  tabular  |
+-----------------------------------------+-----------+
| 3 : [opt] Variables of interest         |  txt      |
+-----------------------------------------+-----------+

2. Block Y structure
Block Y is in tabular format (.tsv).
This table contains the name of the samples in the first column.
The other columns correspond to phenotypes.
For each of these other columns, a column determines which sample is associated with a phenotype (value equals to 1) or not (value equals to 0). The names of the samples in Block Y (transposed), in the sample metadata (transposed) and for all datasets have to be in the same order.

3. Variables of interest structure
All the variables of interest are in the same column.

----------
Parameters
----------

@HELP_MANUAL@

------------
Output files
------------

viscorvar_matcoraddvar_output.RData
    RData output

viscorvar_matcoraddvar_response_var.tsv


viscorvar_matcoraddvar_blocks_comb.tsv


    ]]></help>

    <expand macro="citations" />

</tool>