ONT-bacpac-nf

:wrench: THIS PIPELINE IS UNDER ACTIVE DEVELOPMENT :wrench:

WIP title, WIP workflow.

Workflow description

A rapid and portable workflow for pond-side sequencing of bacterial pathogens for sustainable aquaculture using ONT long-read sequencing.

User guide

For Gadi specific docs see docs/gadi-execution.md

Developer notes

Fast, iterative testing is best done within an interactive session on Gadi. Start an interactive session with the following command:

qsub -I -P <PROJECT> -lwalltime=2:00:00 -lmem=190GB -lncpus=24 -qnormal -lstorage=scratch/<PROJECT>

Once the session starts, you'll need to move back to your ONT-bacpac-nf directory. Execute the pipeline with:

bash test/run_test.sh

Keep in mind:

• No external network access on job queues, except copyq
• Downloading kraken2 database is currently slowest step, so its best to download once and reuse it by providing the --kraken2_db parameter to the pipeline
• Will explore faster and more secure download method for all reference datasets with aria2

Ensure you do the following:

• Break down tasks into modules, with distinct functions
• Clearly define input and output channels with descrptive names
• Add comments within your code to explain the logic and purpose of complex sections
• Use configuration files to manage parameters, separating code from configuration
• Provide sensible default values
• Design modules to fail early if prerequisites are not met or if an error occurs
• Implement comprehensive Groovy logging with log.info
• Specify resource requirements for each process
• Use dynamic resource handling to adjust resource requests based on input data size, where possible
• Use Singularity to excecute biocontainers or Wave containers
• Exploit parallelism by designing processes to run concurrently wherever possible
• Consult the benchmarking results to optimise process resource requirements

Please use this structure for modules and saves these files as run_process.nf:

process process_name {
  tag "ADD A TAG THAT CAPTURES TASK LEVEL INFO"
  container '<link to container>'

  input:
    tuple val(barcode), path <input>

  output:
  path("*"), emit: process_out

  script: 
  """
  # EXPLAIN THE PROCESS 
  ADD CODE 
  """
}

Component tools

Additional notes

Help / FAQ / Troubleshooting

License(s)

Acknowledgements/citations/credits