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Advisor(s)
Abstract(s)
Biosciences have been revolutionised by NGS technologies in last years, leading to new perspectives in medical, industrial and environmental applications. And although our motivation comes from biosciences, the following is true for many areas of science: published results are usually hard to reproduce, delaying the adoption of new methodologies and hindering innovation. Even if data and tools are freely available, pipelines for data analysis are in general barely described and their setup is far from trivial. NGSPipes addresses these issues reducing the efforts necessary to define, build and deploy pipelines, either at a local workstation or in the cloud. NGSPipes framework is freely available at http://ngspipes.github.io/.
Description
Keywords
Scientific workflows Reproducible science Domain specific languages Decentralised computing
Citation
DANTAS, Bruno; [et al] – NGSPipes: fostering reproducibility and scalability in biosciences, In ACM-BCB '17 Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology,and Health Informatics. Boston, Massachusetts, USA: ACM-BCB`17, 2017. ISBN: 978-1-4503-4722-8. Pp. 603-603
Publisher
Association for Computing Machinery