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Nextflow is workflow management software which enables the writing of scalable and reproducible scientific workflows. It can integrate various software package and environment management systems such as Docker, Singularity, and Conda. It allows for existing pipelines written in common scripting languages, such as R and Python, to be seamlessly coupled together. It implements a Domain Specific Language (DSL) that simplifies the implementation and running of workflows on cloud or high-performance computing (HPC) infrastructures.

This lesson also introduces nf-core: a community-driven platform, which provide peer reviewed best practice analysis pipelines written in Nextflow.

This lesson motivates the use of Nextflow and nf-core as development tools for building and sharing reproducible data science workflows.

lesson objectives

1. The learner will understand the fundamental components of a Nextflow script, including channels, processes and operators.
2. The learner will write a multi-step workflow script to align, quantify, and perform QC on an RNA-Seq data in Nextflow DSL.
3. The learner will be able to write a Nextflow configuration file to alter the computational resources allocated to a process.
4. The learner will use nf-core to run a community curated pipeline, on an RNA-Seq dataset.

Prerequisites

This is an intermediate lesson and assumes familiarity with the core materials covered in the [Software Carpentry Lessons] [swc-lessons]. In particular learners need to be familiar with material covered in The Unix Shell. It is helpful to be familiar with using another programming language, to the level of Plotting and Programming in Python or R for Reproducible Scientific Analysis, although this lesson does not specifically rely on Python or R. No previous knowledge of Nextflow, other workflow software, or Groovy is required. {: .prereq}

{: .prereq}

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