comparison dada2_makeSequenceTable.xml @ 3:c3834c230b0a draft

planemo upload for repository https://github.com/bernt-matthias/mb-galaxy-tools/tree/topic/dada2/tools/dada2 commit 5b1603bbcd3f139cad5c876be83fcb39697b5613-dirty

2:d2e7c5f8a9f7

#end if

samples <- list()
#for $s in $samples:
    #if $len($samples) == 1
    samples <- $read_data($s)
    #else
    samples[["$s.element_identifier"]] <- $read_data($s)
    #end if
#end for
## make sequence table
seqtab <- makeSequenceTable(samples, orderBy = "$orderby")


reads.per.seqlen <- tapply(colSums(seqtab), factor(nchar(getSequences(seqtab))), sum)
df <- data.frame(length=as.numeric(names(reads.per.seqlen)), count=reads.per.seqlen)

#if $plot == "yes"
pdf( '$plot_output' )
ggplot(data=df, aes(x=length, y=count)) + 
    geom_col() + 
#if $filter_cond.filter_select != "no"
    geom_vline( xintercept=c($filter_cond.min-0.5, $filter_cond.max+0.5) ) + 
#end if
    theme_bw()
bequiet <- dev.off()
#end if

write.table(seqtab, "$stable", quote=F, sep="\t", row.names = T, col.names = NA)
    ]]></configfile>
    </configfiles>
    <inputs>
        <param name="samples" type="data" multiple="true" format="@DADA_UNIQUES@" label="samples" />
        <param name="orderby" type="select" label="Column order">
            <option value="abundance">abundance</option>
            <option value="nsamples">nsamples</option>
        </param>
        <conditional name="filter_cond">
            <param name="filter_select" type="select" label="Filter method">
                <option value="no">No filter</option>
                <option value="minmax">Specify minimum and maximum sequence lengths</option>
            </param>
            <when value="no"/>
            <when value="minmax">

        <data name="stable" format="dada2_sequencetable" label="${tool.name} on ${on_string}"/>
        <data name="plot_output" format="pdf" label="${tool.name} on ${on_string}: sequence length distribution">
            <filter>plot</filter>
        </data>
    </outputs>

    <help><![CDATA[
This function constructs a sequence table (analogous to an OTU table) from the provided list of
samples.

Custom Reference data sets
--------------------------

For ** taxonomy assignment ** the following is needed: 

- a reference fasta data base 
- a comma separated list of taxonomic ranks present in the reference data base 

The reference fasta data base for taxonomic assignment (fasta or compressed fasta) needs to encode the taxonomy corresponding to each sequence in the fasta header lines in the following fashion (note, the second sequence is not assigned down to level 6):

::

    >Level1;Level2;Level3;Level4;Level5;Level6;
    ACCTAGAAAGTCGTAGATCGAAGTTGAAGCATCGCCCGATGATCGTCTGAAGCTGTAGCATGAGTCGATTTTCACATTCAGGGATACCATAGGATAC
    >Level1;Level2;Level3;Level4;Level5;
    CGCTAGAAAGTCGTAGAAGGCTCGGAGGTTTGAAGCATCGCCCGATGGGATCTCGTTGCTGTAGCATGAGTACGGACATTCAGGGATCATAGGATAC

The list of required taxonomic ranks could be for instance: "Kingdom,Phylum,Class,Order,Family,Genus"

The reference data base for ** species assignment ** is a fasta file (or compressed fasta file), with the id line formatted as follows:

::

    >ID Genus species
    ACCTAGAAAGTCGTAGATCGAAGTTGAAGCATCGCCCGATGATCGTCTGAAGCTGTAGCATGAGTCGATTTTCACATTCAGGGATACCATAGGATAC
    >ID Genus species
    CGCTAGAAAGTCGTAGAAGGCTCGGAGGTTTGAAGCATCGCCCGATGGGATCTCGTTGCTGTAGCATGAGTACGGACATTCAGGGATCATAGGATAC
    ]]></help>
    <expand macro="citations"/>
</tool>

3:c3834c230b0a

#end if

samples <- list()
#for $s in $samples:
    #if $len($samples) == 1
    samples <- readRDS('$s')
    #else
    samples[["$s.element_identifier"]] <- readRDS('$s')
    #end if
#end for
## make sequence table
seqtab <- makeSequenceTable(samples, orderBy = "$orderBy")


reads.per.seqlen <- tapply(colSums(seqtab), factor(nchar(getSequences(seqtab))), sum)
df <- data.frame(length=as.numeric(names(reads.per.seqlen)), count=reads.per.seqlen)

#if $plot == "yes"
pdf( '$plot_output' )
ggplot(data=df, aes(x=length, y=count)) +
    geom_col() +
#if $filter_cond.filter_select != "no"
    geom_vline( xintercept=c($filter_cond.min-0.5, $filter_cond.max+0.5) ) +
#end if
    theme_bw()
bequiet <- dev.off()
#end if

write.table(seqtab, "$stable", quote=F, sep="\t", row.names = T, col.names = NA)
    ]]></configfile>
    </configfiles>
    <inputs>
        <param name="samples" type="data" multiple="true" format="@DADA_UNIQUES@" label="samples" />
        <param argument="orderBy" type="select" label="Column order">
            <option value="abundance">abundance</option>
            <option value="nsamples">nsamples</option>
        </param>
        <conditional name="filter_cond">
            <param name="filter_select" type="select" label="Length filter method">
                <option value="no">No filter</option>
                <option value="minmax">Specify minimum and maximum sequence lengths</option>
            </param>
            <when value="no"/>
            <when value="minmax">

        <data name="stable" format="dada2_sequencetable" label="${tool.name} on ${on_string}"/>
        <data name="plot_output" format="pdf" label="${tool.name} on ${on_string}: sequence length distribution">
            <filter>plot</filter>
        </data>
    </outputs>
    <tests>
        <test>
            <param name="samples" ftype="dada2_mergepairs" value="mergePairs_F3D0.Rdata"/>
            <output name="stable" value="makeSequenceTable_F3D0.tab" ftype="dada2_sequencetable" />
        </test>
    </tests>
    <help><![CDATA[
Description
...........

This function constructs a sequence table -- more precisely an amplicon sequence variant table (ASV) table -- a higher-resolution version of the OTU table produced by traditional methods.

The sequence table is a matrix with rows corresponding to (and named by) the samples, and columns corresponding to (and named by) the sequence variants.

Usage
.....

**Input**: The result of derepFastq, dada, or mergePairs.

**Output**: A data set of type dada2_sequencetable, i.e. a tabular with a row for each sample, and a column for each unique sequence across all the samples. The columns are named by the sequence.

Details
.......

Sequences that are much longer or shorter than expected may be the result of non-specific priming. You can remove non-target-length by applying a length filter. This is analogous to “cutting a band” in-silico to get amplicons of the targeted length.

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