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PhenoMeNal: Processing and analysis of metabolomics data in the cloud

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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