Experiences with workflows for automating data-intensive bioinformatics.

Spjuth O, Bongcam-Rudloff E, Hernández GC, Forer L, Giovacchini M, Guimera RV, Kallio A, Korpelainen E, Kańduła MM, Krachunov M, Kreil DP, Kulev O, Łabaj PP, Lampa S, Pireddu L, Schönherr S, Siretskiy A, Vassilev D

Biol. Direct 10 (-) 43 [2015-08-19; online 2015-08-19]

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.

Affiliated researcher

PubMed 26282399

DOI 10.1186/s13062-015-0071-8

Crossref 10.1186/s13062-015-0071-8

pii: 10.1186/s13062-015-0071-8
pmc: PMC4539931


Publications 9.5.1