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Nextflow enables scalable and reproducible scientific workflows using software containers such as Docker and Singularity. It allows the adaptation of pipelines written in the most common scripting languages such as R and Python. Nextflow is a Domain Specific Language (DSL) that simplifies the implementation and the deployment of complex parallel and reactive workflows on clouds and clusters.

This lesson also introducesnf-core: a framework that provides a community-driven, peer reviewed platform for the development of best practice analysis pipelines written in Nextflow.

This lesson motivates the use of Nextflow and nf-core as a development tool for building and sharing computational pipelines that facilitate reproducible (data) science workflows.

We welcome all contributions to improve the lesson! Maintainers will do their best to help you if you have anyquestions, concerns, or experience any difficulties along the way.

We'd like to ask you to familiarize yourself with ourContribution Guide and have a look atthe [more detailed guidelines][lesson-example] on proper formatting, ways to render the lesson locally, and evenhow to write new episodes.

Please see the current list of [issues][https://github.com/carpentries-incubator/workflows-nextflow/issues] for ideas for contributing to thisrepository. For making your contribution, we use the GitHub flow, which isnicely explained in the chapterContributing to a Project in Pro Gitby Scott Chacon.Look for the tag. This indicates that the maintainers will welcome a pull request fixing this issue.

Current maintainers of this lesson are

• Graeme R. Grimes
• Mahesh Binzer-Panchal

A list of contributors to the lesson can be found inAUTHORS

To cite this lesson, please consult withCITATION

• Carpentries Development Handbook
• community-lessons
• lesson-example