Scalable workflows and reproducible data analysis for genomics

Francesco Strozzi, Roel Janssen, Ricardo Wurmus, Michael R. Crusoe, George Githinji, Paolo Di Tommaso, Dominique Belhachemi, Steffen Möller, Geert Smant, Joep de Ligt, Pjotr Prins*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

15 Citations (Scopus)


Biological, clinical, and pharmacological research now often involves analyses of genomes, transcriptomes, proteomes, and interactomes, within and between individuals and across species. Due to large volumes, the analysis and integration of data generated by such high-throughput technologies have become computationally intensive, and analysis can no longer happen on a typical desktop computer. In this chapter we show how to describe and execute the same analysis using a number of workflow systems and how these follow different approaches to tackle execution and reproducibility issues. We show how any researcher can create a reusable and reproducible bioinformatics pipeline that can be deployed and run anywhere. We show how to create a scalable, reusable, and shareable workflow using four different workflow engines: The Common Workflow Language (CWL), Guix Workflow Language (GWL), Snakemake, and Nextflow. Each of which can be run in parallel. We show how to bundle a number of tools used in evolutionary biology by using Debian, GNU Guix, and Bioconda software distributions, along with the use of container systems, such as Docker, GNU Guix, and Singularity. Together these distributions represent the overall majority of software packages relevant for biology, including PAML, Muscle, MAFFT, MrBayes, and BLAST. By bundling software in lightweight containers, they can be deployed on a desktop, in the cloud, and, increasingly, on compute clusters. By bundling software through these public software distributions, and by creating reproducible and shareable pipelines using these workflow engines, not only do bioinformaticians have to spend less time reinventing the wheel but also do we get closer to the ideal of making science reproducible. The examples in this chapter allow a quick comparison of different solutions.

Original languageEnglish
Title of host publicationEvolutionary Genomics
Subtitle of host publicationStatistical and Computational Methods
PublisherHumana Press Inc.
ISBN (Electronic)9781493990740
ISBN (Print)9781493990733
Publication statusPublished - 6 Jul 2019

Publication series

NameMethods in Molecular Biology
ISSN (Print)1064-3745


  • Big data
  • Bioconda
  • Bioinformatics
  • Cloud computing
  • Cluster computing
  • Common Workflow Language
  • CWL
  • Debian Linux
  • Evolutionary biology
  • GNU Guix
  • Guix Workflow Language
  • MPI
  • MrBayes
  • Nextflow
  • Parallelization
  • Snakemake
  • Virtual machine


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