Open and reproducible bioinformatics with Nextflow and nf-core
Reproducibility is at the heart of the scientific method, both in the lab and also for data analysis. Workflow managers such as Nextflow (https://www.nextflow.io/) allow researchers to chain the steps of an analysis together into a single pipeline that can be executed in a highly reproducible manner. Nextflow pipelines are portable and work with different types of analysis servers, High Performance Computing (HPC) Clusters as well as multiple cloud computing providers.
Here I describe nf-core (https://nf-co.re/), a community effort to collect a curated set of analysis pipelines built using Nextflow. All nf-core pipelines adhere to a strict set of best-practice guidelines to reach their full potential for FAIR analysis (Findable, Accessible, Interoperable and Reusable). Started in 2018 the community now has hundreds of contributors with 45 different pipelines covering different data and analysis types, ranging from genomics to proteomics and even image analysis. Pipelines are well tested, well documented and are ready for anyone to use.
How to watch
The meeting will be on Zoom (https://zoom.us/j/98115333040?pwd=bHhuOFZhSksxVndWcTNMY1VUaXlTdz09) and also be available on YouTube (https://www.youtube.com/channel/UCexVPLCSwS2poahjxuewZNg).
Speaker bio
Phil Ewels (@ewels) is the Team Leader for Bioinformatics development at the National Genomics Infrastructure (NGI) at SciLifeLab in Stockholm, Sweden. SciLifeLab is a national centre for molecular biosciences. The NGI offers genomic library preparation, sequencing and bioinformatics analysis support for research groups across the country.
Phil did his PhD and postdoc in epigenetics at the University of Cambridge and Babraham Institute in Cambridge, UK and has now been in Sweden for six years. He enjoys creating bioinformatics tools that have a focus on user friendliness such as MultiQC, nf-core and SRA-explorer. Now at SciLifeLab, he and his team focus on the development and scaling up of new lab protocols and bioinformatics solutions. They develop new analysis pipelines and try to ensure that the tools they write are scalable, reproducible and transferable.