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Experiences with workflows for automating data-intensive bioinformatics

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...

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Detalles Bibliográficos
Autores principales: Spjuth, Ola, Bongcam-Rudloff, Erik, Hernández, Guillermo Carrasco, Forer, Lukas, Giovacchini, Mario, Guimera, Roman Valls, Kallio, Aleksi, Korpelainen, Eija, Kańduła, Maciej M, Krachunov, Milko, Kreil, David P, Kulev, Ognyan, Łabaj, Paweł P., Lampa, Samuel, Pireddu, Luca, Schönherr, Sebastian, Siretskiy, Alexey, Vassilev, Dimitar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4539931/
https://www.ncbi.nlm.nih.gov/pubmed/26282399
http://dx.doi.org/10.1186/s13062-015-0071-8
Descripción
Sumario: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. Reviewers This article was reviewed by Dr Andrew Clark.