annotate ipapy2_compute_all_adducts.xml @ 0:f85a6d4e44b0 draft default tip

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

<tool id="ipapy2_compute_all_adducts" name="ipaPy2 compute all adducts" version="@TOOL_VERSION@+galaxy0" profile="@PROFILE@">
    <description>compute the compound database with adducts</description>
    <macros>
        <import>macros.xml</import>
    </macros>
    
    <expand macro="requirements"/>

    <command detect_errors="exit_code"><![CDATA[
        python3 '${__tool_directory__}/ipapy2_compute_all_adducts.py'
        --input_dataset_adduct '${adducts_data}' '${adducts_data.ext}'
        --input_dataset_database ${MS1_DB} ${MS1_DB.ext}
        --ionisation ${ionisation}
        --output_dataset '${all_adducts}' '${all_adducts.ext}'
        --ncores \${GALAXY_SLOTS:-1}
    ]]></command>
    <inputs>
        <param label="Adducts data" name="adducts_data" type="data" format="csv,tsv,tabular,parquet" help="A csv,tsv,tabular or parquet file containing information on all possible adducts."/>
        <param label="MS database" name="MS1_DB" type="data" format="csv,tsv,tabular,parquet" help="A csv,tsv,tabular or parquet file containing the MS1 database."/>
        <expand macro="ionisation"/>
    </inputs>

    <outputs>
        <data label="${tool.name} on ${on_string}" name="all_adducts" format_source="adducts_data"/>
    </outputs>
    
    <tests>
        <test>
            <param name="adducts_data" value="adducts.csv"/>
            <param name="MS1_DB" value="MS1_DB.csv"/>
            <param name="ionisation" value="1"/>
            <output name="all_adducts" file="all_adducts.csv"/>
        </test>
    </tests>
    
    <help><![CDATA[

.. _ipapy2_compute_all_adducts:

=========================================
ipaPy2 Compute All Adducts Tool
=========================================

**Tool Description**

This tool calculates all possible combinations of adducts and compounds given the adduct and compound (MS1) databases. The resulting table is essential for downstream annotation steps in the ipaPy2 workflow.

It is recommended to avoid repeating this step unless necessary—reuse a previously calculated adducts database whenever possible. If you need to compute a new adducts database, include only the adducts you expect in your data (e.g., only the relevant ionization mode, multimers, or adducts based on your mobile phase).

Inputs
------

1. **Adducts data**  
   A file (CSV, TSV, Tabular, or Parquet) containing information on all possible adducts.

2. **MS database**  
   A file (CSV, TSV, Tabular, or Parquet) containing the MS1 compound database.

3. **Ionisation mode**  
   Specify the ionisation mode relevant for your experiment.

Outputs
-------

- **all_adducts**  
  A table containing all possible adduct-compound combinations, suitable for use in downstream annotation tools.

Example of `adducts.csv` file
-----------------------------

.. list-table:: Example adducts.csv
   :header-rows: 1

   * - name
     - calc
     - Charge
     - Mult
     - Mass
     - Ion_mode
     - Formula_add
     - Formula_ded
     - Multi
   * - [M+H]+
     - 1.0073
     - 1
     - 1
     - 1.0073
     - positive
     - H
     - FALSE
     - 1
   * - [M+Na]+
     - 22.9892
     - 1
     - 1
     - 22.9892
     - positive
     - Na
     - FALSE
     - 1
   * - [M+K]+
     - 38.9632
     - 1
     - 1
     - 38.9632
     - positive
     - K
     - FALSE
     - 1

Notes
-----

- Only include adducts relevant to your experiment to reduce database size and improve annotation accuracy.
- The tool supports multiple file formats for flexibility.

References
----------

- For more details on adduct computation and usage in metabolomics annotation, refer to the ipaPy2 documentation or associated publications.

    ]]></help>

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