Nextflow and nf-core: Reproducible Workflows for the Scientific Community
Ellen Sherwood (KTH Royal Institute of Technology)
To support a fast-growing, community-building software for infrastructure agnostic, open source biomedical pipelines.
Biomedical research has become increasingly data-driven. Advances in sequencing and imaging technologies have posed fundamental challenges for the maintenance and analysis of high throughput data. To address these challenges, scientific workflow frameworks are proving to be pivotal tools that fulfill the compliance of data analysis and management to FAIR (Findable, Accessible, Interoperable and Re-usable) standards. Since its first release in 2013, Nextflow has become a leading workflow development software. With approximately 6,000 monthly active users, thousands of GitHub projects and independent software communities forming around it, Nextflow is helping to create the next generation of infrastructure agnostic, open source data analysis workflows. The nf-core community was formed in this context with the primary goal of providing a set of high-quality scientific data analysis workflows written in Nextflow. Workflows hosted on the nf-core framework must adhere to a set of strict best practice guidelines that ensure reproducibility, portability and scalability. Continuous integration testing, extensive usage and output documentation are other prerequisites, and downstream tools are continually evolving to aid in the development and usage of nf-core workflows. The primary objective of this application is to sustain the Nextflow and nf-core projects through maintenance of the codebase, documentation, community support and advocacy while also addressing strategic elements from the technical and community roadmaps. The core principles of both Nextflow and nf-core empower anyone to transparently create, deploy and share their work with the world. Using the latest technology, community initiatives and open source principles, they are helping to drive biomedical discovery.