In this paper we present MASTR-MS, the first wholly functional, open-source LIMS solutions specifically designed for metabolomics laboratories. 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. A number of LIMS have been developed or adapted from other applications for curating metabolomics experiments and data management (i.e. LIMS are software solutions that aim to manage the entire workflow of a laboratory. Scientific journals are also increasingly requesting that experimental data and metadata associated with metabolomics experiments are made available to the scientific community (, ), leading to the establishment of data repositories, such as MetaboLights (Haug et al. Major funding agencies, such as Europe’s Horizon 2020 ( ), the NIH ( ), The Wellcome Trust ( ) and Australia’s NHMRC ( ) have established Data Management Plans that researchers are expected to follow in order to capture, store and share data generated by their grants. Data handling extends beyond collection and curation of raw data, to the management of metadata that defines how the raw data is generated. 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 many cases, these analytical platforms are located in institutional and/or national core facilities that offer a range of metabolomics capabilities to researchers (, ,, , ). ![]() 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. 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. It is freely available under the GNU GPL v3 licence and can be accessed from. This software is being developed in close consultation with members of the metabolomics research community. It acts as an electronic notebook, facilitating project management within a single laboratory or a multi-node collaborative environment. It captures the entire lifecycle of a sample starting from project and experiment design to sample analysis, data capture and storage. MASTR-MS is a comprehensive LIMS solution specifically designed for metabolomics. 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. 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. 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. 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.
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