<?xml version="1.0"?>
<macros>
    <xml name="requirements">
        <requirements>
            <requirement type="package" version="@DADA2_VERSION@">bioconductor-dada2</requirement>
            <yield/>
        </requirements>
    </xml>

    <token name="@DADA2_VERSION@">1.10.0</token>
    <token name="@WRAPPER_VERSION@">4</token>

    <xml name="version_command">
        <version_command><![CDATA[
echo $(R --version | grep version | grep -v GNU)", dada2 version" $(R --vanilla --slave -e "library(dada2); cat(sessionInfo()\$otherPkgs\$dada2\$Version)" 2> /dev/null | grep -v -i "WARNING: ")
        ]]></version_command>
    </xml>

    <xml name="stdio">
        <stdio>
            <regex match="Error: cannot allocate" source="stderr" level="fatal_oom" description="Out of memory error occurred" />
            <regex match="'Calloc' could not allocate memory" source="stderr" level="fatal_oom" description="Out of memory error occurred" />
        </stdio>
    </xml>

    <xml name="citations">
        <citations>
            <citation type="doi">10.1038/nmeth.3869</citation>
            <yield/>
        </citations>
    </xml>

    <token name="@DADA_UNIQUES@">dada2_derep,dada2_dada,dada2_mergepairs</token>

    <!-- function to read dada2 data types
         - derep, dada, and mergepairs are simply read as RDS
         - sequence_table is a named integer matrix (rows=samples, columns=ASVs)
         - uniques is a named integer vector (columns=ASVs, only one rows)-->
    <token name="@READ_FOO@"><![CDATA[
    read.uniques <- function ( fname ) {
         p <- read.table(fname, header=F, sep="\t")
         n <-x[,2]
         names(n)<-x[,1]
    }
    #def read_data($dataset)
        #if $dataset.is_of_type('dada2_sequencetable')
            t(as.matrix( read.table('$dataset', header=T, sep="\t", row.names=1) ))
        #else if $dataset.is_of_type('dada2_uniques')
            read.uniques('$dataset')
        #else if $dataset.is_of_type('tabular')
            read.table('$dataset', header=T, sep="\t", row.names=1)
        #else
            readRDS('$dataset')
        #end if
    #end def
    ]]></token>
    <!-- function to write dada2 data types (the content or the R variable 'out' is written)
         - derep, dada, and mergepairs are written as RDS
         - sequence_table is a named integer matrix (rows=samples, columns=ASVs)
         - uniques is a named integer vector (columns=ASVs, only one rows)-->
    <token name="@WRITE_FOO@"><![CDATA[
write.data <- function( data, fname, type ){
    if( type == 'dada2_uniques'){
        write.table(data, file = fname, quote = F, sep = "\t", row.names = T, col.names = F)
    }else if( type== 'dada2_sequencetable'){
        write.table(t(data), file=fname, quote=F, sep="\t", row.names = T, col.names = NA)
    }else{
        saveRDS(data, file=fname)
    }
}
    ]]></token>

    <xml name="fastq_input" token_multiple="" token_collection_type="" token_argument_fwd="" token_argument_rev="">
        <conditional name="paired_cond">
            <param name="paired_select" type="select" label="Paired reads">
                <option value="paired">paired - in a data set pair</option>
                <option value="separate">paired - in two separate data sets</option>
                <option value="single">single</option>
            </param>
            <when value="paired">
                <param name="reads" argument="@ARGUMENT_FWD@/@ARGUMENT_REV@" type="data_collection" collection_type="@COLLECTION_TYPE@" format="fastq,fastq.gz" label="Paired short read data"/>
            </when>
            <when value="separate">
                <param name="reads" argument="@ARGUMENT_FWD@" type="data" format="fastq,fastq.gz" multiple="@MULTIPLE@" label="Forward read data"/>
                <param name="sdaer" argument="@ARGUMENT_REV@" type="data" format="fastq,fastq.gz" multiple="@MULTIPLE@" label="Reverse read data"/>
            </when>
            <when value="single">
                <param name="reads" argument="@ARGUMENT_FWD@" type="data" format="fastq,fastq.gz" multiple="@MULTIPLE@" label="Short read data"/>
            </when>
        </conditional>
    </xml>

    <!-- for filterAndTrim -->
    <xml name="trimmers">
        <section name="trim" title="Trimming parameters">
            <param argument="truncQ" type="integer" value="2" min="0" label="Truncate reads at quality threshold" help="Truncate reads at the first instance of a quality score less than or equal to this threshold"/>
            <param argument="trimLeft" type="integer" value="0" min="0" label="Trim start of each read" help="The number of nucleotides to remove from the start of each read."/>
            <param argument="trimRight" type="integer" value="0" min="0" label="Trim end of each read" help="The number of nucleotides to remove from the end of each read"/>
            <param argument="truncLen" type="integer" value="0" min="0" label="Truncate read length" help="Truncate reads after this amount of bases. Reads shorter than this are discarded. (default 0: no truncation)"/>
        </section>
    </xml>
    <xml name="filters">
        <section name="filter" title="Filtering parameters">
            <param argument="maxLen" type="integer" value="" optional="true" min="0" label="Remove long reads" help="Remove reads with length greater than this value. Default: no length threshold"/>
            <param argument="minLen" type="integer" value="20" min="0" label="Remove short reads" help="Remove reads with length less than this value. Default: 20"/>
            <param argument="maxN" type="integer" value="0" min="0" label="Remove reads with more Ns" help="Note that some of the subsequent dada pipeline steps do not allow Ns"/>
            <param argument="minQ" type="integer" value="0" min="0" label="Remove low quality reads" help="Reads contain a quality score less than this value will be discarded"/>
            <param argument="maxEE" type="integer" value="" optional="true" min="0" label="Remove reads by number expected errors" help="Reads with a higher number of expected errors (EE) will be discarded, where EE = sum(10^(-Q_i/10)), with Q are the nominal quality scores at the read positions"/>
        </section>
    </xml>

    <xml name="errorEstimationFunction">
        <param name="errfoo" argument="errorEstimationFunction" type="select" label="Error function">
            <option value="loessErrfun">loess: Use a loess fit to estimate error rates from transition counts</option>
            <option value="noqualErrfun">noqual: Estimate error rates for each type of transition while ignoring quality scores.</option>
            <option value="PacBioErrfun">PacBio: Estimate error rates from transition counts in PacBio CCS data.</option>
        </param>
    </xml>
    <token name="@HELP_OVERVIEW@"><![CDATA[
Overview
........

The intended use of the dada2 tools for paired sequencing data is shown in the following image.

.. image:: pairpipe.png

For single end data you the steps "Unzip collection" and "mergePairs" are not necessary.

More information may be found on the dada2 homepage:: https://benjjneb.github.io/dada2/index.html (in particular tutorials) or the documentation of dada2's R package https://bioconductor.org/packages/release/bioc/html/dada2.html (in particular the pdf which contains the full documentation of all parameters)
    ]]></token>
</macros>
