Nextflow enables reproducible computational workflows

genomepy: download genomes the easy way

“…It is essential that experiments are analyzed in a reproducible manner. Computational workflow systems allow for automation of analysis pipelines, that scale from personal computers to HPC and cloud environments (Koster and Rahmann 2012;Di Tommaso et al 2017;Vivian et al 2017). While standardized solutions exist for installation of software and analysis tools ("Pip," n.d.; "Bioconda," n.d.), data download often has to either be performed manually or be scripted on a caseby-case basis.…”

Using the Nextflow framework for reproducible in-silico omics analyses across clusters and clouds

“…When the same pipeline was factored into Nextflow with Docker, the results were identical across platforms. Nextflow was first introduced at BOSC 2015 8 . Over the last year it has attracted an increasing amount of interest within the bioinformaticians community, including numerous users from leading institutions such as the Joint Genome Institute, the Pasteur Institute, the Sanger Institute, the International Agency for Research on Cancer and the Weill Cornell Medical College among others.…”

A Review of Scalable Bioinformatics Pipelines

“…Both the Dockerfile and the resulting container can be moved between machines without installing additional software, and the container can be rerun later with the exact same libraries. Containers can be orchestrated for parallel execution using, for example, Kubernetes (https://kubernetes.io/) or Docker Swarm (https://github.com/docker/swarm), and there are now multiple pipelining tools that use Docker or provide Docker container support including Nextflow [26], Toil [22], Pachyderm (http://www.pachyderm.io/), Luigi (https:// github.com/spotify/luigi) [27], Rabix/bunny [28], and our own walrus system (http://github.com/fjukstad/walrus).…”