<tool id="cfsan_centriflaken" name="Centriflaken" version="0.2.0+galaxy0">
    <description>An automated pipeline to generate a MAG of interest (E.coli or Salmonella) and perform serotyping.</description>
    <requirements>
	<requirement type="package" version="22.04">nextflow</requirement>
	<requirement type="package">graphviz</requirement>
    </requirements>    
    <version_command>nextflow -version</version_command>
    <command detect_errors="exit_code"><![CDATA[
	mkdir -p cpipes-input || exit 1;
    pwd_path=\$(pwd);
    #import os
    #if (str($input_read_type_cond.input_read_type) == "single_long"):
	    #for $key in $input_read_type_cond.input.keys()
	        ln -sf '$input_read_type_cond.input[$key]' './cpipes-input/$key';
	    #end for
    #elif (str($input_read_cond.input_read_type) == "paired"):
        #for $key in $input_read_type_cond.input_pair.keys()
            #set $read_R1 = os.path.basename($input_read_type_cond.input_pair[$key]['forward'])
            #set $read_R2 = os.path.basename($input_read_type_cond.input_pair[$key]['reverse'])
	        ln -sf '$input_read_type_cond.input_pair[$key]['forward']' './cpipes-input/$read_R1';
            ln -sf '$input_read_type_cond.input_pair[$key]['reverse']' './cpipes-input/$read_R2';
	    #end for
    #end if
	$__tool_directory__/0.2.1/cpipes
    --pipeline $input_read_type_cond.pipeline
    #if ($input_read_type_cond.pipeline_cond.pipeline == "centriflaken"):
        --fq_single_end true
        --flye_genome_size '${genome_size}'
        #if ($input_read_type_cond.pipeline_cond.long_read_platform == "nanopore_corr"):
            --flye_nano_corr true --flye_nano_raw false
        #elif ($input_read_type_cond.pipeline_cond.long_read_platform == "nanopore_hq"):
            --flye_nano_hq true --flye_nano_raw false
        #elif ($input_read_type_cond.pipeline_cond.long_read_platform == "pacbio_raw"):
            --flye_pacbio_raw true --flye_nano_raw false
        #elif ($input_read_type_cond.pipeline_cond.long_read_platform == "pacbio_corr"):
            --flye_pacbio_corr true --flye_nano_raw false
        #elif ($input_read_type_cond.pipeline_cond.long_read_platform == "pacbio_hifi"):
            --flye_pacbio_hifi true --flye_nano_raw false
        #end if
    #elif ($input_read_type_cond.pipeline_cond.pipeline == "centriflaken_hy"):
        #if (str($input_read_cond.input_read_type) == "single_long"):
            --fq_single_end true
        #elif (str($input_read_cond.input_read_type) == "paired"):
            --fq_single_end false --fq2_suffix '${input_read_cond.fq2_suffix}'
        #end if
    #end if
	--input \${pwd_path}/cpipes-input
	--output \${pwd_path}/cpipes-output
    --fq_suffix '${input_read_cond.fq_suffix}'
    #if ($fq_filter_by_len != ""):
        --fq_filter_by_len $fq_filter_by_len
    #end if
	--fq_filename_delim '${fq_filename_delim}'
	--fq_filename_delim_idx $fq_filename_delim_idx
	--centrifuge_extract_bug '${centrifuge_extract_bug}'
	-profile kondagac;
    mv './cpipes-output/${pipeline}-multiqc/multiqc_report.html' './multiqc_report.html' || exit 1;
    mv './cpipes-output/${pipeline}-results/kraken2_extract_contigs' kraken2_extract_contigs || exit 1;
    rm -rf ./cpipes-output || exit 1;
    rm -rf ./work || exit 1
    ]]></command>
    <inputs>
        <conditional name="input_read_type_cond">
            <param name="input_read_type" type="select" label="Select the read collection type">
                <option value="single_long" selected="true">Unpaired reads (i.e. Single-End short reads/Long reads)</option>
                <option value="paired">Paired-End reads</option>
            </param>
            <when value="single_long">
                <param name="input" type="data_collection" collection_type="list" format="fastq,fastq.gz,fastqsanger.gz,fastqsanger"
                    label="Dataset list of unpaired short reads / long reads" />
                <conditional name="pipeline_cond">
                    <param name="pipeline" type="select" label="CPIPES Workflow name"
                        help="centriflaken: for long reads (Nanopore or PacBio). centriflaken_hy: for short reads (paired or unpaired). Default: centriflaken">
                        <option value="centriflaken" selected="true">centriflaken</option>
                        <option value="centriflaken_hy">centriflaken_hy</option>
                    </param>
                    <when value="centriflaken">
                        <param name="long_read_platform" type="select" label="Mention long read sequencing platform and type">
                            <option value="nanopore_raw" selected="true">Nanopore raw reads, pre-Guppy5 (&lt;20% error)</option>
                            <option value="nanopore_corr">Nanopore reads that were corrected with other methods (&lt;3% error)</option>
                            <option value="nanopore_hq">Nanopore high-quality reads, Guppy5+ SUP or Q20 (5% error)</option>
                            <option value="pacbio_raw">PacBio regular CLR reads (&lt;20% error)</option>
                            <option value="pacbio_corr">PacBio reads that were corrected with other methods (&lt;3% error)</option>
                            <option value="pacbio_hifi">PacBio HiFi reads (&lt;1% error)</option>
                        </param>
                    </when>
                    <when value="centriflaken_hy">
                        <param name="long_read_platform" value="N/A" type="text" optional="true" label="Mention long read sequencing platform and type"
                            help="THIS OPTION IS IGNORED IF THE INPUT READS ARE SHORT READS."/>
                    </when>
                </conditional>
                <param name="fq_suffix" value=".fastq.gz" type="text" label="Suffix of the R1 FASTQ or Unpaired FASTQ"/>
            </when>
            <when value="paired">
                <param name="input_pair" type="data_collection" collection_type="list:paired" format="fastq,fastq.gz,fastqsanger.gz,fastqsanger"
                    label="List of Dataset pairs" />
                <param name="fq_suffix" value=".fastq.gz" type="text" label="Suffix of the R1 FASTQ or Unpaired FASTQ"/>
                <param name="fq2_suffix" value="_R2_001.fastq.gz" type="text" label="Suffix of the R2 FASTQ"/>
            </when>
        </conditional>
        <param name="fq_filter_by_len" optional="true" value="" type="integer" label="Enter minimum read length to retain before starting the analysis"
            help="Keep this option empty to use default values. Default for centriflaken (long reads) is 4000 bp and for centriflaken_hy (short reads) is 75 bp."/>
        <param name="fq_filename_delim" type="text" value="_" label="File name delimitor by which samples are grouped together (--fq_filename_delim)" 
            help="This is the delimitor by which samples are grouped together to display in the final MultiQC report. For example, if your input data sets are mango_replicate1.fastq.gz, mango_replicate2.fastq.gz, orange_replicate1_maryland.fastq.gz, orange_replicate2_maryland.fastq.gz, then to create 2 samples mango and orange, the value for --fq_filename_delim would be _ (underscore) and the value for --fq_filename_delim_idx would be 1, since you want to group by the first word (i.e. mango or orange) after splitting the filename based on _ (underscore)."/>
        <param name="fq_filename_delim_idx" type="integer" value="1" label="File name delimitor index (--fq_filename_delim_idx)" />
        <param name="centrifuge_extract_bug" type="text" value="Escherichia coli" label="Reads belonging to this taxa are extracted and a MAG is generated to allow for serotyping"/>
        <param name="genome_size" type="text" optional="true" value="5.5m" label="Estimated genome size" help="For example, 5m or 2.6g.">
            <validator type="regex" message="Genome size must be a float  or integer, optionally followed by the a unit prefix (kmg)">^([0-9]*[.])?[0-9]+[kmg]?$</validator>
        </param>
        <!-- <param name="runtime_profile" type="select" label="Run time profile">
            <option value="kondagac" selected="true">conda</option>
            <option value="cingularitygac">singularity</option>
        </param> -->
    </inputs>
    <outputs>
        <data name="multiqc_report" format="html" label="${input_read_type_cond.pipeline_cond.pipeline}: MultiQC Report on ${on_string}" from_work_dir="multiqc_report.html"/>
        <collection name="assembled_mags" type="list" label="${input_read_type_cond.pipeline_cond.pipeline}: Assembled MAGs on ${on_string}">
            <discover_datasets pattern="(?P&lt;name&gt;.*)\.assembly_filtered_contigs\.fasta" ext="fasta" directory="kraken2_extract_contigs"/>
        </collection>
    </outputs>
    <tests>
        <!--Test 01: long reads-->
        <test expect_num_outputs="2">
            <param name="input">
                <collection type="list">
                    <element name="FAL11127.fastq.gz" value="FAL11127.fastq.gz" />
                    <element name="FAL11341.fastq.gz" value="FAL11341.fastq.gz" />
                    <element name="FAL11342.fastq.gz" value="FAL11342.fastq.gz" />
                </collection>
            </param>
            <param name="fq_suffix" value=".fastq.gz"/>
            <output name="multiqc_report" file="multiqc_report.html" ftype="html" compare="sim_size"/>
            <!-- <output name="assembled_mags" file="FAL11127.assembly_filtered.contigs.fasta" ftype="fasta" compare="sim_size"/> -->
        </test>
    </tests>
    <help><![CDATA[

.. class:: infomark

**Purpose**

Centriflaken suite of automated data analysis pipelines are based on Nextflow DSL2 developed at CFSAN, FDA. These pipelines allow rapid 
and effective construction of metagenomic assembled genomes (MAGs) to enable bacterial source-tracking. It is based on methods described in our 
previous publication (Maguire *et al*, 2021. doi: https://doi.org/10.1371/journal.pone.0245172).

----

.. class:: infomark

**Testing and Validation**

The CPIPES - Centriflaken Nextflow pipeline has been wrapped to make it work in Galaxy. It takes in either paired or unpaired short reads or long reads, generates MAGs and performs 
in silico-based analysis (i.e., virulence gene finding). Additionally, AMR gene finding analysis is also included in Centriflaken and performed on MAGs 
of interest. The final summary plots and tables can be downloaded from the provided MultiQC HTML report generated as part of the pipeline. 
The Centriflaken pipeline was validated with data from our previously published method (Maguire *et al*, 2021. doi: https://doi.org/10.1371/journal.pone.0245172) and was able to replicate the detection 
and classification of STECs for each sample. We tested the pipeline with Nanopore data obtained from 21 additional enriched samples from 
irrigation water and was able to perform the entire precision metagenomics analysis in less than 5 hours for all of them. All the original testing and validation was 
done on the command line on the CFSAN Raven2 HPC Cluster.


----

.. class:: infomark

**Outputs**

The main output files are:

    ::

        - MultiQC Report: Contains a brief summary report including any serotyping and AMR result tables.
                          Please note that due to MultiQC customizations, the preview (eye icon) will not
                          work within Galaxy for the MultiQC report. Please download the file by clicking
                          on the floppy icon and view it in your browser on your local desktop/workstation.
        - Final assembly: contains contigs and possibly scaffolds.

  ]]></help>
    <citations>
        <citation type="bibtex">
            @misc{gitlabCPIPES,
            author = {Konganti, Kranti},
            year = {2022},
            title = {CPIPES - Centriflaken},
            publisher = {GitLab},
            journal = {GitLab repository},
            url = {https://cfsan-git.fda.gov/Kranti.Konganti/cpipes}}
        </citation>
    </citations>
</tool>