Journal:MASTR-MS: A web-based collaborative laboratory information management system (LIMS) for metabolomics
| Full article title | MASTR-MS: A web-based collaborative laboratory information management system (LIMS) for metabolomics |
|---|---|
| Journal | Metabolomics |
| Author(s) | Hunter, A.; Dayalan, S.; De Souza, D.; Power, B.; Lorrimar, R.; Szabo, T.; Nguyen, T.; O'Callaghan, S.; Hack, J.; Pyke, J.; Nahid, A.; Barrero, R.; Roessner, U.; Likic, V.; Tull, D.; Bacic, A.; McConville, M.; Bellgard, M. |
| Author affiliation(s) | Murdoch University, The University of Melbourne, The Australian Wine Research Institute |
| Primary contact | Email: malcolmm at unimelb dot edu dot au -or- mbellgard at ccg dot murdoch dot edu dot au |
| Year published | 2017 |
| Volume and issue | 13 (2) |
| Page(s) | 14 |
| DOI | 10.1007/s11306-016-1142-2 |
| ISSN | 1573-3890 |
| Distribution license | Creative Commons Attribution 4.0 International |
| Website | https://link.springer.com/article/10.1007/s11306-016-1142-2 |
| Download | https://link.springer.com/content/pdf/10.1007%2Fs11306-016-1142-2.pdf (PDF) |
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Abstract
Background
An increasing number of research laboratories and core analytical facilities around the world are developing high throughput metabolomic analytical and data processing pipelines that are capable of handling hundreds to thousands of individual samples per year, often over multiple projects, collaborations and sample types. At present, there are no laboratory information management systems (LIMS) that are specifically tailored for metabolomics laboratories that are capable of tracking samples and associated metadata from the beginning to the end of an experiment, including data processing and archiving, and which are also suitable for use in large institutional core facilities or multi-laboratory consortia as well as single laboratory environments.
Results
Here we present MASTR-MS, a downloadable and installable LIMS solution that can be deployed either within a single laboratory or used to link workflows across a multisite network. It comprises a node management system that can be used to link and manage projects across one or multiple collaborating laboratories; a user management system which defines different user groups and privileges of users; a quote management system where client quotes are managed; a project management system in which metadata is stored and all aspects of project management, including experimental setup, sample tracking and instrument analysis, are defined; and a data management system that allows the automatic capture and storage of raw and processed data from the analytical instruments to the LIMS.
Conclusion
MASTR-MS is a comprehensive LIMS solution specifically designed for metabolomics. It captures the entire lifecycle of a sample, starting from project and experiment design to sample analysis, data capture and storage. It acts as an electronic notebook, facilitating project management within a single laboratory or a multi-node collaborative environment. This software is being developed in close consultation with members of the metabolomics research community. It is freely available under the GNU GPL v3 license and can be accessed from https://muccg.github.io/mastr-ms/.
Keywords
MASTR-MS, metabolomics, LIMS, omics
Introduction
Metabolomic approaches aim to detect and quantitate levels of all small molecules in a biological system and, together with other "omic" approaches, can be used to generate a systems-wide understanding of biological processes. Metabolomic approaches typically involve the use of advanced mass spectrometry and nuclear magnetic resonance (NMR) spectrometry platforms to maximize coverage of the chemically diverse metabolites that make up biological systems. In many cases, these analytical platforms are located in institutional and/or national core facilities that offer a range of metabolomics capabilities to researchers.[1][2][3][4][5] These core facilities, as well as individual research groups with sophisticated metabolomics infrastructure and capability are faced with the challenge of tracking large numbers of samples and the associated metadata, and linking this information with the raw datasets generated by multiple analytical platforms, as well as processed down-stream data sets. Data handling extends beyond collection and curation of raw data, to the management of metadata that defines how the raw data is generated. Major funding agencies, such as Europe’s Horizon 2020[5], the NIH[6], The Wellcome Trust[7] and Australia’s NHMRC[8] have established data management plans that researchers are expected to follow in order to capture, store and share data generated by their grants. Scientific journals are also increasingly requesting that experimental data and metadata associated with metabolomics experiments are made available to the scientific community[9][10], leading to the establishment of data repositories, such as MetaboLights[11] and Metabolomics Workbench.[12]
LIMS are software solutions that aim to manage the entire workflow of a laboratory. A number of LIMS have been developed or adapted from other applications for curating metabolomics experiments and data management (e.g., SetupX, Sesame). While these LIMS have features that allow capture of project metadata, experiments and samples, data storage, and data sharing, they exhibit a number of limitations around their capacity to accommodate different vendor instruments and have restricted functionalities to facilitate a collaborative configuration between geographically distributed laboratories. In this paper we present MASTR-MS, the first wholly functional, open-source LIMS solution specifically designed for metabolomics laboratories.
Availability and requirements
Project name: MASTR-MS
Project home page: https://muccg.github.io/mastr-ms/
Operating system(s): Server Installation: Centos 6.x (x86_64); Client: Any operating system and modern web browser can be used as the web client to access MASTR-MS; DataSync Client: Linux or Windows
Programming language: Python 2.7
Software requirements: Apache 2.2 or higher, PostgreSQL 8.4 or higher
License: GNU GPL v3
Any restrictions to use by non-academics: See GNU GPL v3
Acknowledgements
This project is supported by Bioplatforms Australia Ltd., the Australian National Collaborative Research Infrastructure Strategy Program and the Education Investment Fund Super Science Initiative. The authors gratefully acknowledge additional funding from the Australian National Health and Medical Research Council (APP634485, APP1055319) and the EU FP7 Project (HEALTH.2012.2.1.1-1-C): RD Connect: An integrated platform connecting databases, registries, biobanks and clinical bioinformatics for rare disease research. MJM is a NHMRC Principal Research Fellow. AB acknowledges the support of the ARC Centre of Excellence in Plant Cell Walls. The authors acknowledge the many contributions made by other researchers in the Bioplatforms Australia network, including Michael Clarke, Hayden Walker, Dorothee Hayne, Robert Trengove and Catherine Rawlinson.
Adam Hunter, Saravanan Dayalan and David De Souza have contributed equally to this work.
Compliance with ethical standards
Conflict of interest
All authors declare that they have no conflicts of interest.
Ethical approval
This article does not contain any studies with human participants or animals performed by any of the authors.
Supplementary material
Supplementary material 1 (JPG 137 KB)
Supplementary material 2 (PNG 48 KB)
Supplementary material 3 (PNG 6836 KB)
Supplementary material 4 (PNG 3593 KB)
Supplementary material 5 (PNG 2913 KB)
References
- ↑ "Metabolomics Australia". Metabolomics Australia. http://www.metabolomics.net.au/. Retrieved 05 December 2014.
- ↑ "The Metabolomics Inovation Centre". University of Alberta. http://www.metabolomicscentre.ca/. Retrieved 05 December 2014.
- ↑ "Metabolomics". The Common Fund. National Institutes of Health, Office of Strategic Coordination. http://commonfund.nih.gov/metabolomics/index. Retrieved 05 December 2014.
- ↑ "MetaboHUB". MetaboHUB Centre INRA Bordeaux - Aquitaine. http://www.metabohub.fr/. Retrieved 05 December 2014.
- ↑ 5.0 5.1 "Guidelines on FAIR Data Management in Horizon 2020 - Version 3.0" (PDF). European Commission. 26 July 2016. http://ec.europa.eu/research/participants/data/ref/h2020/grants_manual/hi/oa_pilot/h2020-hi-oa-data-mgt_en.pdf. Retrieved 05 December 2014.
- ↑ "NIH Data Sharing Policy and Implementation Guidance". Grants and Funding. National Institutes of Health. 5 March 2003. https://grants.nih.gov/grants/policy/data_sharing/data_sharing_guidance.htm. Retrieved 05 December 2014.
- ↑ "Guidance for researchers: Developing a data management and sharing plan". Policy and position statements. Wellcome Trust. 2014. Archived from the original on 18 October 2014. https://web-beta.archive.org/web/20141018165611/http://www.wellcome.ac.uk/About-us/Policy/Spotlight-issues/Data-sharing/Guidance-for-researchers/index.htm. Retrieved 05 December 2014.
- ↑ "Australian Code for the Responsible Conduct of Research". National Health and Medical Research Council, Australia. 2007. https://www.nhmrc.gov.au/guidelines-publications/r39. Retrieved 05 December 2014.
- ↑ "Data Policies". Nature. Macmillan Publishers Limited. https://www.nature.com/sdata/policies/data-policies. Retrieved 05 December 2014.
- ↑ "Instructions for authors: Research Articles". GigaScience. BioMed Central Ltd. 2014. Archived from the original on 15 May 2014. https://web.archive.org/web/20140515012736/http://www.gigasciencejournal.com:80/authors/instructions/research. Retrieved 05 December 2014.
- ↑ Haug, K.; Salek, R.M.; Conesa, P. (2013). "MetaboLights--An open-access general-purpose repository for metabolomics studies and associated meta-data". Nucleic Acids Research 41 (D1): D781-6. doi:10.1093/nar/gks1004. PMC PMC3531110. PMID 23109552. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3531110.
- ↑ "Metabolics Workbench". University of California San Diego. http://www.metabolomicsworkbench.org/. Retrieved 05 December 2014.
Notes
This presentation is faithful to the original, with only a few minor changes to presentation. In some cases important information was missing from the references, and that information was added. The original article's references were in alphabetical order; the references here are shown in order of appearance in the article due to the way the wiki processes references. In several cases the original URL had changed; an archived version of the URL was used instead.
