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11 results on '"Spjuth, Ola"'

4. PhenoMeNal: processing and analysis of metabolomics data in the cloud

Author

Peters, Kristian, primary, Bradbury, James, additional, Bergmann, Sven, additional, Capuccini, Marco, additional, Cascante, Marta, additional, de Atauri, Pedro, additional, Ebbels, Timothy M D, additional, Foguet, Carles, additional, Glen, Robert, additional, Gonzalez-Beltran, Alejandra, additional, Günther, Ulrich L, additional, Handakas, Evangelos, additional, Hankemeier, Thomas, additional, Haug, Kenneth, additional, Herman, Stephanie, additional, Holub, Petr, additional, Izzo, Massimiliano, additional, Jacob, Daniel, additional, Johnson, David, additional, Jourdan, Fabien, additional, Kale, Namrata, additional, Karaman, Ibrahim, additional, Khalili, Bita, additional, Emami Khonsari, Payam, additional, Kultima, Kim, additional, Lampa, Samuel, additional, Larsson, Anders, additional, Ludwig, Christian, additional, Moreno, Pablo, additional, Neumann, Steffen, additional, Novella, Jon Ander, additional, O'Donovan, Claire, additional, Pearce, Jake T M, additional, Peluso, Alina, additional, Piras, Marco Enrico, additional, Pireddu, Luca, additional, Reed, Michelle A C, additional, Rocca-Serra, Philippe, additional, Roger, Pierrick, additional, Rosato, Antonio, additional, Rueedi, Rico, additional, Ruttkies, Christoph, additional, Sadawi, Noureddin, additional, Salek, Reza M, additional, Sansone, Susanna-Assunta, additional, Selivanov, Vitaly, additional, Spjuth, Ola, additional, Schober, Daniel, additional, Thévenot, Etienne A, additional, Tomasoni, Mattia, additional, van Rijswijk, Merlijn, additional, van Vliet, Michael, additional, Viant, Mark R, additional, Weber, Ralf J M, additional, Zanetti, Gianluigi, additional, and Steinbeck, Christoph, additional

Published
2018
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10. Recommendations on e-infrastructures for next-generation sequencing

Author

Spjuth, Ola, Bongcam-Rudloff, Erik, Dahlberg, Johan, Dahlö, Martin, Kallio, Aleksi, Pireddu, Luca, Vezzi, Francesco, and Korpelainen, Eija

Subjects
Next-generation sequencing, Cloud computing, E-infrastructure, High-performance computing
Abstract

With ever-increasing amounts of data being produced by next-generation sequencing (NGS) experiments, the requirements placed on supporting e-infrastructures have grown. In this work, we provide recommendations based on the collective experiences from participants in the EU COST Action SeqAhead for the tasks of data preprocessing, upstream processing, data delivery, and downstream analysis, as well as long-term storage and archiving. We cover demands on computational and storage resources, networks, software stacks, automation of analysis, education, and also discuss emerging trends in the field. E-infrastructures for NGS require substantial effort to set up and maintain over time, and with sequencing technologies and best practices for data analysis evolving rapidly it is important to prioritize both processing capacity and e-infrastructure flexibility when making strategic decisions to support the data analysis demands of tomorrow. Due to increasingly demanding technical requirements we recommend that e-infrastructure development and maintenance be handled by a professional service unit, be it internal or external to the organization, and emphasis should be placed on collaboration between researchers and IT professionals.

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11. PhenoMeNal: processing and analysis of metabolomics data in the cloud.

Author

Peters K, Bradbury J, Bergmann S, Capuccini M, Cascante M, de Atauri P, Ebbels TMD, Foguet C, Glen R, Gonzalez-Beltran A, Günther UL, Handakas E, Hankemeier T, Haug K, Herman S, Holub P, Izzo M, Jacob D, Johnson D, Jourdan F, Kale N, Karaman I, Khalili B, Emami Khonsari P, Kultima K, Lampa S, Larsson A, Ludwig C, Moreno P, Neumann S, Novella JA, O'Donovan C, Pearce JTM, Peluso A, Piras ME, Pireddu L, Reed MAC, Rocca-Serra P, Roger P, Rosato A, Rueedi R, Ruttkies C, Sadawi N, Salek RM, Sansone SA, Selivanov V, Spjuth O, Schober D, Thévenot EA, Tomasoni M, van Rijswijk M, van Vliet M, Viant MR, Weber RJM, Zanetti G, and Steinbeck C

Subjects
Cloud Computing, Humans, Workflow, Metabolomics methods, Software
Abstract

Background: Metabolomics is the comprehensive study of a multitude of small molecules to gain insight into an organism's metabolism. The research field is dynamic and expanding with applications across biomedical, biotechnological, and many other applied biological domains. Its computationally intensive nature has driven requirements for open data formats, data repositories, and data analysis tools. However, the rapid progress has resulted in a mosaic of independent, and sometimes incompatible, analysis methods that are difficult to connect into a useful and complete data analysis solution., Findings: PhenoMeNal (Phenome and Metabolome aNalysis) is an advanced and complete solution to set up Infrastructure-as-a-Service (IaaS) that brings workflow-oriented, interoperable metabolomics data analysis platforms into the cloud. PhenoMeNal seamlessly integrates a wide array of existing open-source tools that are tested and packaged as Docker containers through the project's continuous integration process and deployed based on a kubernetes orchestration framework. It also provides a number of standardized, automated, and published analysis workflows in the user interfaces Galaxy, Jupyter, Luigi, and Pachyderm., Conclusions: PhenoMeNal constitutes a keystone solution in cloud e-infrastructures available for metabolomics. PhenoMeNal is a unique and complete solution for setting up cloud e-infrastructures through easy-to-use web interfaces that can be scaled to any custom public and private cloud environment. By harmonizing and automating software installation and configuration and through ready-to-use scientific workflow user interfaces, PhenoMeNal has succeeded in providing scientists with workflow-driven, reproducible, and shareable metabolomics data analysis platforms that are interfaced through standard data formats, representative datasets, versioned, and have been tested for reproducibility and interoperability. The elastic implementation of PhenoMeNal further allows easy adaptation of the infrastructure to other application areas and 'omics research domains., (© The Author(s) 2018. Published by Oxford University Press.)

Published
2019
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