<tool id="albacore_denoise" name="Albacore de-noise" version="0.001">

    <description>Filter noise from barcode bins</description>

    <!-- ***************************************************************** -->
   
    <!--
    <requirements>
        <requirement type="package" version="1.2.6">albacore</requirement>
    </requirements>
    -->

    <!-- ***************************************************************** -->

    <version_command>echo "0.001"</version_command>

    <!-- ***************************************************************** -->

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

    perl $__tool_directory__/denoise.pl

        --table $table

        #if $filter.type == 'topN'
          --n_keep ${filter.n_keep}
        #else
          --min_score ${filter.min_score}
          --min_frac  ${filter.min_frac}
        #end if

        $remove_unclassified

        #for $input in $inputs
            --input ${input}
            --name  ${input.name}
        #end for

        --summary $summary

    ]]>
    </command>

    <!-- ***************************************************************** -->

    <inputs>

        <param name="inputs" type="data_collection" collection_type="list" format="fast5_archive" label="Input reads" multiple="true" />
        <param name="table" type="data" format="tabular" label="Read table" />
        <conditional name="filter">
            <param name="type" type="select" label="Filtering type">
                <option value="cutoffs" selected="true">By cutoff</option>
                <option value="topN">Top N bins</option>
            </param>
            <when value="cutoffs">
                <param name="min_score" value="70" type="float" min="0" max="100" label="Minimum average score (0-100)" />
                <param name="min_frac" value="0.05" type="float" min="0" label="Minimum fraction of average count" />
            </when>
            <when value="topN">
                <param name="n_keep" value="1" type="integer" min="1" label="Number of top bins to keep" />
            </when>
        </conditional>
        <param name="remove_unclassified" type="boolean" checked="true" truevalue="--remove_unclassified" falsevalue="" label="Remove unclassified reads" />

    </inputs>

    <!-- ***************************************************************** -->

    <outputs>

        <collection type="list" name="outputs" label="${tool.name} on ${on_string} (reads)">
            <discover_datasets pattern="(?P&lt;name&gt;.*)\.fast5\.tar\.gz$" directory="outputs" format="fast5_archive" />
        </collection>

        <data name="summary" format="tabular" label="${tool.name} on ${on_string} (summary)" />

    </outputs>

    <!-- ***************************************************************** -->

    <!--
    <tests>
        <test>
            <param name="input" value="test_data.fast5.tar.gz" ftype="fast5_archive" />
            <output name="output" file="test_data.fastq" compare="diff" />
        </test>
    </tests>
    -->

    <!-- ***************************************************************** -->

    <help>
    <![CDATA[

**Description**

This script will filter "noise" bins from the barcoded output of Albacore
based on read counts and mean quality scores for each barcode bin. It can
either filter the top N bins (if you know the number of barcodes in your
sample) or filter based on minimum read count (as ratio to average value over
all bin) and minimum average score.

    ]]>
    </help>

    <!-- ***************************************************************** -->
    
    <citations>
    </citations>

</tool>