Dantas, BrunoFleitas, CameneliasAlmeida, AlexandreForja, JoãoFrancisco, AlexandreSimão, JoséVaz, Cátia2018-02-222018-02-222017-08DANTAS, 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. 603-603978-1-4503-4722-8http://hdl.handle.net/10400.21/8103Biosciences 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/.engScientific workflowsReproducible scienceDomain specific languagesDecentralised computingconference object10.1145/3107411.3108213