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Build Nextflow Pipeline

Get the workspace ready:

  1. Visit - Can't find link, download the repository folder. Now the files and folders in the repository holds the following details:

  2. Update the data, modules and files as per your requirement - resource to understand this better can be found here -Nextflow training

    • Data - Data folder should be updated with all the relevant fq files
    • Module - Its basically a stand-alone module scripts that can be included and shared across multiple workflows. Each module can contain its own process or workflow definition.

    Each pipeline can be divided into stand alone modules, where the DSL language can be used to define the input, and output structure:

    Example: ```
    process fastqc { cpus 2

        publishDir "${params.fastqc_outdir}", mode: 'copy', overwrite: false
        tuple val(sample_id), file(reads)
        fastqc -t 2 -o "./" -f fastq -q ${reads}


    Understand how modules work via the .nf files under modules folder in the repository

    • - Is the main nextflow script which imports all the modules to run. This allows you to store these components in a separate file(s) so that they can be reused in multiple workflows.

    Sections under the file:

    2.1. Define your params:

    params.reads = "$baseDir/data/ggal/ggal_gut_{1,2}.fq" params.fastqc_outdir= "FASTQC" params.multiqc_outdir= "MULTIQC"

    2.2. Define your polly workspace:

    params.workspace_id = 9810

    Import Modules : include {fastqc} from './module/' params(params) include {multiqc} from './module/' params(params) include {pollySync_fastqc} from './module/' params(params) include {pollySync_multiqc} from './module/' params(params)

    2.3. Message:

    ``` """

    Nextflow on K8s with DSL2 modules | TUTORIAL

    pipeline reads : ${params.reads} fastqc output directory : ${params.fastqc_outdir} multiqc output directory : ${params.multiqc_outdir} polly workspace id : ${params.workspace_id} ============================================= """ .stripIndent() ```

    2.4. Main script:

    workflow { read_pairs_ch = channel.fromFilePairs( params.reads, checkIfExists: true ) fastqc(read_pairs_ch) pollySync_fastqc(fastqc.output.collect()) multiqc(fastqc.output.collect()) pollySync_multiqc(multiqc.output.collect()) }

    2.5. Completion handler

    workflow.onComplete { println ( workflow.success ? "\nWorkflow completed. Enjoy! \n" : "Oops .. something went wrong" ) }

    3. Create a folder in your workspace, give a relevant name, here we have used demo as a name, upload the downloaded and updated repository files and folder from step 1 and 2 from local to Polly workspace.


    Using Polly CLI function the local files can be synced to the workspace

    To upload the downloaded and updated repository from step 3 and 4 from local to Polly workspace, by using the following command:

    polly files sync --workspace-id --source --destination Workspace ID of the workspace where the data is being synced has to be mentioned in the --workspace-id option. Source and destination can be Polly workspace path as well as local path. Workspace path should start with polly:// followed by the directory path in the workspace where the data is to be synced. Here polly:// is the root directory for the mentioned workspace.

    polly files sync --workspace-id 9810 --source ./ --destination polly://Demo