How I Teach Life Scientists…to Build Reproducible, Scalable Workflows with Nextflow

The term “reproducible research” has been used to describe the idea that a scientific publication should be distributed along with all the raw data and metadata used in the study, all the code and/or computational notebooks needed to produce results...

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How I Teach Life Scientists…to Build Reproducible, Scalable Workflows with Nextflow

Sateesh Peri, Bioinformatics Developer | Training Specialist (Leidos | CDC)

Format: Short talk and demo

Abstract

The term “reproducible research” has been used to describe the idea that a scientific publication should be distributed along with all the raw data and metadata used in the study, all the code and/or computational notebooks needed to produce results from the raw data, and the computational environment or a complete description thereof. The standardization, portability and reproducibility of analysis pipelines are key issues within the bioinformatics community. Being able to reproduce scientific results is the central tenet of the scientific method. However, moving toward FAIR (findable, accessible, interoperable and reusable) research methods in data-driven science is complex.

I will be presenting the lessons learned and feedback from organizing short-format workshops for building data analysis pipelines using nextflow, an incredibly powerful and flexible workflow language. I will also introduce the nf-core framework as a means for the development of collaborative, peer-reviewed, best-practice analysis pipelines. Through open discussion and collaboration among the community, it is possible to leverage the knowledge of experts across the world for the development of domain-specific pipelines and the implementation of current best-practice analysis methods. This collaborative process bypasses the traditional barriers that can exist between research groups, resulting in high-quality pipelines that anyone can use.

I will give a walk-through for the nextflow tutorial – variant calling edition and introduce Gitpod to the community where you can try the exercises in an online computing environment at your own pace, with the course material in another window alongside.

Resources

Tutorial Link: https://sateeshperi.github.io/nextflow_varcal/nextflow/

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