Abstract
BackgroundAn 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.ConclusionMASTR-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 licence and can be accessed from, https://muccg.github.io/mastr-ms/.
Highlights
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
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
In this paper we present MASTR-MS, the first wholly functional, open-source Laboratory Information Management Systems (LIMS) solutions designed for metabolomics laboratories
Summary
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 NMR 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 (http://www.metabolomics.net.au, http:// www.metabolomicscentre.ca, http://commonfund.nih.gov/ metabolomics/index, http://www.metabohub.fr/en/, http:// ec.europa.eu/research/participants/data/ref/h2020/grants_ manual/hi/oa_pilot/h2020-hi-oa-data-mgt_en.pdf). These analytical platforms are located in institutional and/or national core facilities that offer a range of metabolomics capabilities to researchers (http://www.metabolomics.net.au, http:// www.metabolomicscentre.ca, http://commonfund.nih.gov/ metabolomics/index, http://www.metabohub.fr/en/, http:// ec.europa.eu/research/participants/data/ref/h2020/grants_ manual/hi/oa_pilot/h2020-hi-oa-data-mgt_en.pdf) 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. Electronic supplementary material The online version of this article (doi:10.1007/s11306-016-1142-2) contains supplementary material, which is available to authorized users.
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