Experiences with workflows for automating data-intensive bioinformatics
Ola Spjuth,
Erik Bongcam-Rudloff,
Guillermo Carrasco Hernández,
Lukas Forer,
Mario Giovacchini,
Roman Valls Guimera,
Aleksi Kallio,
Eija Korpelainen,
Maciej M Kańduła,
Milko Krachunov,
David P Kreil,
Ognyan Kulev,
Paweł P Łabaj,
Samuel Lampa,
Luca Pireddu,
Sebastian Schönherr,
Alexey Siretskiy,
Dimitar Vassilev
Biology Direct, Volume 10, Number 43 - august 2015
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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.
Références BibTex
@Article{SBCFGVKKKKKKLLPSSV15,
author = {Spjuth, O. and Bongcam-Rudloff, E. and Carrasco Hernández, G. and Forer, L. and Giovacchini, M. and Valls Guimera, R. and Kallio, A. and Korpelainen, E. and Kańduła, M. and Krachunov, M. and Kreil, D. and Kulev, O. and Łabaj, P. and Lampa, S. and Pireddu, L. and Schönherr, S. and Siretskiy, A. and Vassilev, D.},
title = {Experiences with workflows for automating data-intensive bioinformatics},
journal = {Biology Direct},
number = {43},
volume = {10},
month = {august},
year = {2015},
keywords = {Workflow, Automation, Data-intensive, High-performance computing, Big data, Reproducibility},
doi = {10.1186/s13062-015-0071-8},
url = {https://publications.crs4.it/pubdocs/2015/SBCFGVKKKKKKLLPSSV15},
}
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