comparison kraken-filter.xml @ 3:5bee9adae474 draft

planemo upload for repository https://github.com/galaxyproject/tools-iuc/blob/master/tool_collections/kraken/kraken_filter/ commit e8fc7c9dad5f583ad6763ecb9bd8c924832abacd

2:fe94f318048c

<tool id="kraken-filter" name="Kraken-filter" version="1.2.1">
    <description>
        filter classification by confidence score
    </description>
    <macros>
        <import>macros.xml</import>
    </macros>
    <expand macro="requirements" />
    <expand macro="stdio" />
    <expand macro="version_command" />
    <command>
        <![CDATA[
        @SET_DATABASE_PATH@ &&
        kraken-filter @INPUT_DATABASE@ --threshold $threshold "${input}" > "$filtered_output"
        ]]>
    </command>
    <inputs>
        <param format="tabular" label="Kraken output" name="input" type="data" help="Select taxonomy classification produced by kraken"/>
        <param label="Confidence threshold" max="1" min="0" name="threshold" type="float" value="0" help="--threshold; A number between 0 and 1; default=0"/>
        <expand macro="input_database" />
    </inputs>
    <outputs>
        <data format="tabular" name="filtered_output" />
    </outputs>
    <tests>
        <test>
            <param name="input" value="kraken_filter_test1.tab"/>
            <param name="threshold" value="0"/>
            <param name="kraken_database" value="test_db"/>
            <output name="output" file="kraken_filter_test1_output.tab" ftype="tabular"/>
        </test>
    </tests>

    <help>
<![CDATA[

At present, we have not yet developed a confidence score with a solid probabilistic interpretation for Kraken. However, we have developed a simple scoring scheme that has yielded good results for us, and we've made that available in the kraken-filter script. The approach we use allows a user to specify a threshold score in the [0,1] interval; the ``kraken-filter`` script then will adjust labels up the tree until the label's score (described below) meets or exceeds that threshold. If a label at the root of the taxonomic tree would not have a score exceeding the threshold, the sequence is called unclassified by ``kraken-filter``.

A sequence label's score is a fraction C/Q, where C is the number of k-mers mapped to LCA values in the clade rooted at the label, and Q is the number of k-mers in the sequence that lack an ambiguous nucleotide (i.e., they were queried against the database). Consider the example of the LCA mappings in Kraken's output::

 562:13 561:4 A:31 0:1 562:3 

would indicate that::

 the first 13 k-mers mapped to taxonomy ID #562
 the next 4 k-mers mapped to taxonomy ID #561

3:5bee9adae474

<tool id="kraken-filter" name="Kraken-filter" version="@WRAPPER_VERSION@">
    <description>filter classification by confidence score</description>
    <macros>
        <import>macros.xml</import>
    </macros>
    <expand macro="requirements" />
    <expand macro="version_command" />
    <command detect_errors="exit_code"><![CDATA[
        @SET_DATABASE_PATH@ &&

        kraken-filter
            @INPUT_DATABASE@
            --threshold $threshold
            '${input}'
            > '$filtered_output'
    ]]></command>
    <inputs>
        <param name="input" type="data" format="tabular" label="Kraken output" help="Select taxonomy classification produced by kraken"/>
        <param argument="--threshold" type="float" value="0" min="0" max="1"
               label="Confidence threshold" help="A floating point number between 0 and 1; default=0"/>

        <expand macro="input_database" />
    </inputs>
    <outputs>
        <data format="tabular" name="filtered_output" />
    </outputs>
    <tests>
        <test>
            <param name="input" value="kraken_filter_test1.tab"/>
            <param name="threshold" value="0"/>
            <param name="kraken_database" value="test_db"/>

            <output name="filtered_output" file="kraken_filter_test1_output.tab" ftype="tabular"/>
        </test>
    </tests>

    <help>
<![CDATA[

At present, we have not yet developed a confidence score with a solid probabilistic interpretation for Kraken. However, we have developed a simple scoring scheme that has yielded good results for us, and we've made that available in the kraken-filter script. The approach we use allows a user to specify a threshold score in the [0,1] interval; the ``kraken-filter`` script then will adjust labels up the tree until the label's score (described below) meets or exceeds that threshold. If a label at the root of the taxonomic tree would not have a score exceeding the threshold, the sequence is called unclassified by ``kraken-filter``.

A sequence label's score is a fraction C/Q, where C is the number of k-mers mapped to LCA values in the clade rooted at the label, and Q is the number of k-mers in the sequence that lack an ambiguous nucleotide (i.e., they were queried against the database). Consider the example of the LCA mappings in Kraken's output::

 562:13 561:4 A:31 0:1 562:3

would indicate that::

 the first 13 k-mers mapped to taxonomy ID #562
 the next 4 k-mers mapped to taxonomy ID #561