@Article{IPB-2278, author = {Peters, K. and Bradbury, J. and Bergmann, S. and Capuccini, M. and Cascante, M. and de Atauri, P. and Ebbels, T. M. D. and Foguet, C. and Glen, R. and Gonzalez-Beltran, A. and Günther, U. L. and Handakas, E. and Hankemeier, T. and Haug, K. and Herman, S. and Holub, P. and Izzo, M. and Jacob, D. and Johnson, D. and Jourdan, F. and Kale, N. and Karaman, I. and Khalili, B. and Emami Khonsari, P. and Kultima, K. and Lampa, S. and Larsson, A. and Ludwig, C. and Moreno, P. and Neumann, S. and Novella, J. A. and O'Donovan, C. and Pearce, J. T. M. and Peluso, A. and Piras, M. E. and Pireddu, L. and Reed, M. A. C. and Rocca-Serra, P. and Roger, P. and Rosato, A. and Rueedi, R. and Ruttkies, C. and Sadawi, N. and Salek, R. M. and Sansone, S.-A. and Selivanov, V. and Spjuth, O. and Schober, D. and Thévenot, E. A. and Tomasoni, M. and van Rijswijk, M. and van Vliet, M. and Viant, M. R. and Weber, R. J. M. and Zanetti, G. and Steinbeck, C.}, title = {{PhenoMeNal: processing and analysis of metabolomics data in the cloud}}, year = {2019}, pages = {giy149}, journal = {GigaScience}, doi = {10.1093/gigascience/giy149}, url = {https://dx.doi.org/10.1093/gigascience/giy149}, volume = {8}, abstract = {BackgroundMetabolomics 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.FindingsPhenoMeNal (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.ConclusionsPhenoMeNal 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.} }