Abstract

High-throughput technologies, such as next-generation sequencing, have turned molecular biology into a data-intensive discipline, requiring bioinformaticians to use high-performance computing resources and carry out data management and analysis tasks on large scale. Workflow systems can be useful to simplify construction of analysis pipelines that automate tasks, support reproducibility and provide measures for fault-tolerance. However, workflow systems can incur significant development and administration overhead so bioinformatics pipelines are often still built without them. We present the experiences with workflows and workflow systems within the bioinformatics community participating in a series of hackathons and workshops of the EU COST action SeqAhead. The organizations are working on similar problems, but we have addressed them with different strategies and solutions. This fragmentation of efforts is inefficient and leads to redundant and incompatible solutions. Based on our experiences we define a set of recommendations for future systems to enable efficient yet simple bioinformatics workflow construction and execution.

Keywords

Workflow; Automation; Data-intensive; High-performance computing; Big data; Reproducibility

Published in

Biology Direct
2015, Volume: 10, article number: 43

SLU Authors

• Bongcam Rudloff, Erik

  • Department of Animal Biosciences, Swedish University of Agricultural Sciences
    

UKÄ Subject classification

Bioinformatics (Computational Biology)


Publication identifier

DOI: https://doi.org/10.1186/s13062-015-0071-8

Permanent link to this page (URI)

https://res.slu.se/id/publ/68100