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PhenoMeNal: Processing and analysis of metabolomics data in the cloud
File | Description | Size | Format | |
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giy149.pdf | Published version | 2.2 MB | Adobe PDF | View/Open |
Title: | PhenoMeNal: Processing and analysis of metabolomics data in the cloud |
Authors: | 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 Khonsari, PE 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, S-A Selivanov, V Spjuth, O Schober, D Thévenot, EA Tomasoni, M Van Rijswijk, M Van Vliet, M Viant, MR Weber, RJM Zanetti, G Steinbeck, C |
Item Type: | Journal Article |
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 which 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 which 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. |
Issue Date: | 1-Feb-2019 |
Date of Acceptance: | 1-Dec-2018 |
URI: | http://hdl.handle.net/10044/1/65330 |
DOI: | https://dx.doi.org/10.1093/gigascience/giy149 |
ISSN: | 2047-217X |
Publisher: | Oxford University Press |
Journal / Book Title: | GigaScience |
Volume: | 8 |
Issue: | 2 |
Copyright Statement: | © 2018 The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (CC BY 4.0) license (https://creativecommons.org/licenses/by/4.0/). |
Sponsor/Funder: | European Molecular Biology Laboratory Imperial College Healthcare NHS Trust- BRC Funding National Institutes of Health National Institutes of Health |
Funder's Grant Number: | 654241 RDB03 79560 R03CA211631 RO1HL133932 |
Keywords: | Science & Technology Life Sciences & Biomedicine Biology Multidisciplinary Sciences Life Sciences & Biomedicine - Other Topics Science & Technology - Other Topics metabolomics data analysis e-infrastructures NMR mass spectrometry computational workflows galaxy cloud computing standardization statistics MASS-SPECTROMETRY STANDARDS SPECTRA METABOLITES PLATFORM SYSTEM TOOL INTEGRATION ANNOTATION REPOSITORY NMR cloud computing computational workflows data analysis e-infrastructures galaxy mass spectrometry metabolomics standardization statistics Cloud Computing Humans Metabolomics Software Workflow Humans Software Metabolomics Workflow Cloud Computing |
Publication Status: | Published |
Conference Place: | United States |
Article Number: | giy149 |
Online Publication Date: | 2018-12-07 |
Appears in Collections: | School of Public Health Faculty of Engineering |