Browsing by Author "Dantas, Bruno"
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- NGSPipes: fostering reproducibility and scalability in biosciencesPublication . Dantas, Bruno; Fleitas, Camenelias; Almeida, Alexandre; Forja, João; Francisco, Alexandre; Simão, José; Vaz, CátiaBiosciences 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/.
- NGSPipes: from specification to automatic deployment of NGS pipelinesPublication . Dantas, Bruno; Fleitas, Calmenelias; Francisco, Alexandre P.; Simão, José; Vaz, CátiaBiosciences have been revolutionized by next generation sequencing (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 either because data is not available or tools are not readily available, which delays the adoption of new methodologies and hinders innovation. Our focus is on tool readiness and pipelines availability. Even though most tools are freely available, pipelines are in general barely described and their configuration is far from trivial, with many parameters to be tuned.In this paper we discuss how to effectively build and use pipelines, relying on state of the art computing technologies to execute them without users need to configure, install and manage tools, servers and complex workflow management systems. A framework is also proposed showing that we can have public pipelines ready to process and analyse very high volume experimental data, produced for instance by high-throughput technologies, and that can be executed by users without effort. The NGSPipes framework and underlying architecture provides a major step towards open science and true collaboration in what concerns tools and pipelines among computational biology researchers and practitioners, which may share and replicate results in an easier and transparent way.