phoenix.pipeline.xml

<?xml version="1.0" encoding="UTF-8" standalone="yes"?>
<pd:pipeline xmlns:pd="xsd://www.illumina.com/ica/cp/pipelinedefinition" code="phoenix pipeline" version="1.0">
    <pd:dataInputs>
        <pd:dataInput code="input" format="CSV" type="FILE" required="false" multiValue="false">
            <pd:label>input</pd:label>
            <pd:description>A comma-separated (csv) file containing information about the samples in the experiment.</pd:description>
        </pd:dataInput>
        <pd:dataInput code="input_sra" format="CSV" type="FILE" required="false" multiValue="false">
            <pd:label>input_sra</pd:label>
            <pd:description>A csv file that has one SRR number per line. Use with SRA or CDC_SRA entry point.</pd:description>
        </pd:dataInput>
        <pd:dataInput code="input_samples" format="FASTQ, FASTA" type="FILE" required="false" multiValue="true">
            <pd:label>input_samples</pd:label>
            <pd:description>input samples for pipeline. For SCAFFOLDS and CDC_SCAFFOLDS entry points this should be a FASTA file, for PHOENIX and CDC_PHOENIX entry points it should be a FASTQ file. Don't pass any samples if using SRA or CDC_SRA, just pass a text file with one SRR per line to INPUT_SRA.
All files will be staged in workflow.launchDir</pd:description>
        </pd:dataInput>
        <pd:dataInput code="kraken2db" format="TAR" type="FILE" required="true" multiValue="false">
            <pd:label>kraken2db</pd:label>
            <pd:description>Path for where kraken2 database files are, which includes hash.k2d, taxo.k2d, opts.k2d and ktaxonomy.tsv files. You can pass a decompressed folder or in its compressed '.tar.gz' form. The database can be downloaded from https://benlangmead.github.io/aws-indexes/k2 . You must use a database created after 3/14/2023.",
</pd:description>
        </pd:dataInput>
        <pd:dataInput code="project_dirs" format="UNKNOWN" type="DIRECTORY" required="true" multiValue="true">
            <pd:label>project_dirs</pd:label>
            <pd:description>directories (assets, conf, lib, bin, modules, workflows and subworkflows) with additional files/input to run pipeline found on github repo. </pd:description>
        </pd:dataInput>
        <pd:dataInput code="schema_json" format="JSON" type="FILE" required="true" multiValue="false">
            <pd:label>schema_json</pd:label>
            <pd:description>nextflow_schema.json file found on github repo.</pd:description>
        </pd:dataInput>
    </pd:dataInputs>
    <pd:steps>
        <pd:step execution="MANDATORY" code="general">
            <pd:label>general</pd:label>
            <pd:description>general parameters</pd:description>
            <pd:tool code="general parameters">
                <pd:label>general</pd:label>
                <pd:description>general parameters</pd:description>
                <pd:parameter code="mode" minValues="1" maxValues="1" classification="USER">
                    <pd:label>entry</pd:label>
                    <pd:description>State the entry of the pipeline you want to use. The options are PHOENIX, CDC_PHOENIX, SCAFFOLDS, CDC_SCAFFOLDS, SRA and CDC_SRA.",
</pd:description>
                    <pd:stringType/>
                    <pd:value>PHOENIX</pd:value>
                </pd:parameter>
                <pd:parameter code="busco_db_path" minValues="1" maxValues="1" classification="USER">
                    <pd:label>busco_db_path</pd:label>
                    <pd:description>Path (full or relative) for where BUSCO files are if you want to run in offline mode. The database is ~250GB if you download it from https://busco-data.ezlab.org/v5/data/lineages/ . Use only with -entry CDC_PHOENIX, CDC_SCAFFOLDS or CDC_SRA.</pd:description>
                    <pd:stringType/>
                    <pd:value></pd:value>
                </pd:parameter>
                <pd:parameter code="coverage" minValues="1" maxValues="1" classification="USER">
                    <pd:label>coverage</pd:label>
                    <pd:description>Used to increase the coverage cut off >30x.</pd:description>
                    <pd:integerType/>
                    <pd:value>30</pd:value>
                </pd:parameter>
                <pd:parameter code="create_ncbi_sheet" minValues="1" maxValues="1" classification="USER">
                    <pd:label>create_ncbi_sheet</pd:label>
                    <pd:description>Pass this argument to generate partially filled out excel sheets for NCBI upload. This should still be reviewed PRIOR to upload. Only use with -entry CDC_PHOENIX and -entry PHOENIX. As a reminder, please do not submit raw sequencing data to the CDC HAI-Seq BioProject (531911) unless you are a state public health laboratory, a CDC partner or have been directed to do so by DHQP. The BioProject accession IDs in this file are specifically designated for domestic HAI bacterial pathogen sequencing data, including from the Antimicrobial Resistance Laboratory Network (AR Lab Network), state public health labs, surveillance programs, and outbreaks. For inquiries about the appropriate BioProject location for your data, please contact HAISeq@cdc.gov.</pd:description>
                    <pd:booleanType/>
                    <pd:value>false</pd:value>
                </pd:parameter>
            </pd:tool>
        </pd:step>
        <pd:step execution="MANDATORY" code="scaffolds entry parameters">
            <pd:label>SCAFFOLDS and CDC_SCAFFOLDS parameters</pd:label>
            <pd:description>scaffolds entry parameters</pd:description>
            <pd:tool code="scaffolds entry parameters">
                <pd:label>scaffolds entry parameters</pd:label>
                <pd:description>scaffolds entry parameters</pd:description>
                <pd:parameter code="indir" minValues="1" maxValues="1" classification="USER">
                    <pd:label>indir</pd:label>
                    <pd:description>Path to a input directory to search for assemblies. Files with the extention '*.filtered.scaffolds.fa.gz' and '*.renamed.scaffolds.fa.gz' will be ignored. Alternatively, you can pass a samplesheet (columns should be 'sample,assembly') with the --input argument.</pd:description>
                    <pd:stringType/>
                    <pd:value></pd:value>
                </pd:parameter>
                <pd:parameter code="scaffolds_ext" minValues="1" maxValues="1" classification="USER">
                    <pd:label>scaffolds_ext</pd:label>
                    <pd:description>String that is the FULL extension of the scaffolds files you wish to input. For example, use if your file names are {sample_id}.fa.gz use '.fa.gz' and if you want to look through subdirectories for files with the name {sample_id}.fa.gz then use '/*.fa.gz'. A regrex of this extension (ex. *.scaffolds.fa.gz) will then be used as default. Assemblies must end in '.fa.gz' or '.fasta.gz'.</pd:description>
                    <pd:stringType/>
                    <pd:value>.scaffolds.fa.gz</pd:value>
                </pd:parameter>
            </pd:tool>
        </pd:step>
        <pd:step execution="MANDATORY" code="sra entry parameters">
            <pd:label>SRA and CDC_SRA parameters</pd:label>
            <pd:description>sra entry parameters</pd:description>
            <pd:tool code="sra entry parameters">
                <pd:label>sra entry parameters</pd:label>
                <pd:description>sra entry parameters</pd:description>
                <pd:parameter code="use_sra" minValues="1" maxValues="1" classification="USER">
                    <pd:label>use_sra</pd:label>
                    <pd:description>Select true if you want to keep samples named by SRA number rather than sample name found in NCBI metadata.</pd:description>
                    <pd:booleanType/>
                    <pd:value>false</pd:value>
                </pd:parameter>
            </pd:tool>
        </pd:step>
    </pd:steps>
</pd:pipeline>