comparison unifrac.unweighted.xml @ 2:c26d24a77e85 draft

planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/mothur commit 3418f23b9768f5aafb86488f5ec1cb97530d4fb3

1:6c69462bfd5a

    </macros>
    <expand macro="requirements"/>
    <expand macro="stdio"/>
    <expand macro="version_command"/>
    <command><![CDATA[
        @SHELL_OPTIONS@

        ## create symlinks to input datasets
        ln -s "$tree" tree.dat &&
        ln -s "$group" group.dat &&
        ln -s "$name" name.dat &&
        ln -s "$count" count.dat &&

        echo 'unifrac.unweighted(
            tree=tree.dat,
            #if $group:
                group=group.dat,
                #if $groups:
                    groups=${ str($groups).replace(",","-") },
                #end if
            #end if
            #if $name:
                name=name.dat,
            #end if
            iters=$iters,
            #if $subsampling.use == "yes":
                #if $subsampling.subsample:
                    subsample=$subsampling.subsample,
                #else
                    subsample=T,
                #end if
                consensus=$subsampling.consensus,
            #else
                random=$random,
            #end if
            #if $distance:
                distance=$distance,
            #end if
            #if $count:
                count=count.dat,
            #end if
            root=$root,
            processors='\${GALAXY_SLOTS:-1}'
        )'
        | sed 's/ //g'  ## mothur trips over whitespace
        | mothur
        | tee mothur.out.log
    ]]></command>
    <inputs>
        <param name="tree" type="data" format="mothur.tre" label="tree - Tree"/>
        <param name="group" type="data" format="mothur.groups" optional="true" label="group - Group file for the tree"/>
        <param name="groups" type="select" optional="true" multiple="true" label="groups - Select groups for pairwise comparisons">

            <option value="square">Phylip Square Matrix</option>
            <option value="column">Pairwise Distance Matrix</option>
        </param>
        <param name="root" type="boolean" truevalue="true" falsevalue="false" checked="false" label="root - the entire root in your calculations"/>
        <param name="count" type="data" format="mothur.count_table" optional="true" label="count - a count_table" help="generated by count.seqs"/>
    </inputs>
    <outputs>
        <expand macro="logfile-output"/>
        <data name="summary" format="tabular" from_work_dir="tree*.uwsummary" label="${tool.name} on ${on_string}: summary"/>
        <data name="dist" format="mothur.lower.dist" from_work_dir="tree.dat*.dist " label="${tool.name} on ${on_string}: dist">

    <tests>
        <test><!-- test with defaults -->
            <param name="tree" value="abrecovery.tre" ftype="mothur.tre"/>
            <output name="summary" md5="33917fcb36e815ed8924f2ea2729bdc1" ftype="tabular"/>
            <output name="dist" md5="ce65f7d1d2aeb492d8a5373ca18ed5b0" ftype="mothur.lower.dist"/>
            <expand macro="logfile-test"/>
        </test>
        <test><!-- test with random and no subsampling -->
            <param name="tree" value="abrecovery.tre" ftype="mothur.tre"/>
            <param name="random" value="true"/>
            <output name="summary" md5="6aff35274802c4727cbbbc084b7d2dca" ftype="tabular"/>
            <output name="unweighted" md5="9f52d2bd4c5de4c459ae314b6ed83b7a" ftype="tabular"/>
            <expand macro="logfile-test"/>
        </test>
        <test><!-- test with group file and group select -->
            <param name="tree" value="abrecovery.tre" ftype="mothur.tre"/>
            <param name="group" value="abrecovery.groups" ftype="mothur.groups"/>
            <param name="groups" value="A,B"/>
            <param name="distance" value="square"/>
            <output name="summary" md5="a4a0a2faf75cb15bdb049c368dcbe73a" ftype="tabular"/>
            <output name="dist" md5="d215db402049db87cac629470301d5c6" ftype="mothur.square.dist"/>
            <expand macro="logfile-test"/>
        </test>
        <test><!-- test with subsample and consensus -->
            <param name="tree" value="abrecovery.tre" ftype="mothur.tre"/>
            <param name="group" value="abrecovery.groups" ftype="mothur.groups"/>

                    <has_text text="A"/>
                    <has_text text="B"/>
                    <has_text text="C"/>
                </assert_contents>
            </output>
            <expand macro="logfile-test"/>
        </test>
    </tests>
    <help>
<![CDATA[

@MOTHUR_OVERVIEW@

**Command Documentation**

The unifrac.unweighted_ command the unweighted UniFrac algorithm. The unifrac.weighted command implements the weighted version of the command. Both of these methods are available through the UniFrac website. The UniFrac methods are generic tests that describes whether two or more communities have the same structure. The significance of the test statistic can only indicate the probability that the communities have the same structure by chance. The value does not indicate a level of similarity.

.. _unifrac.unweighted: https://www.mothur.org/wiki/Unifrac.unweighted

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

2:c26d24a77e85

    </macros>
    <expand macro="requirements"/>
    <expand macro="stdio"/>
    <expand macro="version_command"/>
    <command><![CDATA[
@SHELL_OPTIONS@

## create symlinks to input datasets
ln -s '$tree' tree.dat &&
ln -s '$group' group.dat &&
ln -s '$name' name.dat &&
ln -s '$count' count.dat &&

echo 'unifrac.unweighted(
    tree=tree.dat,
    #if $group:
        group=group.dat,
        #if $groups:
            groups=${ str($groups).replace(",","-") },
        #end if
    #end if
    #if $name:
        name=name.dat,
    #end if
    iters=$iters,
    #if $subsampling.use == "yes":
        #if $subsampling.subsample:
            subsample=$subsampling.subsample,
        #else
            subsample=T,
        #end if
        consensus=$subsampling.consensus,
    #else
        random=$random,
    #end if
    #if $distance:
        distance=$distance,
    #end if
    #if $count:
        count=count.dat,
    #end if
    root=$root,
    processors='\${GALAXY_SLOTS:-1}'
)'
| sed 's/ //g'  ## mothur trips over whitespace
| mothur
| tee mothur.out.log
    ]]></command>
    <inputs>
        <param name="tree" type="data" format="mothur.tre" label="tree - Tree"/>
        <param name="group" type="data" format="mothur.groups" optional="true" label="group - Group file for the tree"/>
        <param name="groups" type="select" optional="true" multiple="true" label="groups - Select groups for pairwise comparisons">

            <option value="square">Phylip Square Matrix</option>
            <option value="column">Pairwise Distance Matrix</option>
        </param>
        <param name="root" type="boolean" truevalue="true" falsevalue="false" checked="false" label="root - the entire root in your calculations"/>
        <param name="count" type="data" format="mothur.count_table" optional="true" label="count - a count_table" help="generated by count.seqs"/>
        <expand macro="param-savelog"/>
    </inputs>
    <outputs>
        <expand macro="logfile-output"/>
        <data name="summary" format="tabular" from_work_dir="tree*.uwsummary" label="${tool.name} on ${on_string}: summary"/>
        <data name="dist" format="mothur.lower.dist" from_work_dir="tree.dat*.dist " label="${tool.name} on ${on_string}: dist">

    <tests>
        <test><!-- test with defaults -->
            <param name="tree" value="abrecovery.tre" ftype="mothur.tre"/>
            <output name="summary" md5="33917fcb36e815ed8924f2ea2729bdc1" ftype="tabular"/>
            <output name="dist" md5="ce65f7d1d2aeb492d8a5373ca18ed5b0" ftype="mothur.lower.dist"/>
            <param name="savelog" value="true"/>
            <expand macro="logfile-test"/>
        </test>
        <test><!-- test with random and no subsampling -->
            <param name="tree" value="abrecovery.tre" ftype="mothur.tre"/>
            <param name="random" value="true"/>
            <output name="summary" md5="6aff35274802c4727cbbbc084b7d2dca" ftype="tabular"/>
            <output name="unweighted" md5="9f52d2bd4c5de4c459ae314b6ed83b7a" ftype="tabular"/>
            <param name="savelog" value="true"/>
            <expand macro="logfile-test"/>
        </test>
        <test><!-- test with group file and group select -->
            <param name="tree" value="abrecovery.tre" ftype="mothur.tre"/>
            <param name="group" value="abrecovery.groups" ftype="mothur.groups"/>
            <param name="groups" value="A,B"/>
            <param name="distance" value="square"/>
            <output name="summary" md5="a4a0a2faf75cb15bdb049c368dcbe73a" ftype="tabular"/>
            <output name="dist" md5="d215db402049db87cac629470301d5c6" ftype="mothur.square.dist"/>
            <param name="savelog" value="true"/>
            <expand macro="logfile-test"/>
        </test>
        <test><!-- test with subsample and consensus -->
            <param name="tree" value="abrecovery.tre" ftype="mothur.tre"/>
            <param name="group" value="abrecovery.groups" ftype="mothur.groups"/>

                    <has_text text="A"/>
                    <has_text text="B"/>
                    <has_text text="C"/>
                </assert_contents>
            </output>
            <param name="savelog" value="true"/>
            <expand macro="logfile-test"/>
        </test>
    </tests>
    <help><![CDATA[

@MOTHUR_OVERVIEW@

**Command Documentation**

The unifrac.unweighted_ command the unweighted UniFrac algorithm. The unifrac.weighted command implements the weighted version of the command. Both of these methods are available through the UniFrac website. The UniFrac methods are generic tests that describes whether two or more communities have the same structure. The significance of the test statistic can only indicate the probability that the communities have the same structure by chance. The value does not indicate a level of similarity.

.. _unifrac.unweighted: https://www.mothur.org/wiki/Unifrac.unweighted

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