Open source pipelines for integrated metabolomics analysis by NMR and mass spectrometry

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Metabolomics comprises an important suite of techniques in modern Life Sciences research, typically performed by NMR spectroscopy or mass spectrometry (MS), applied in a range of fields for biomarker discovery, as well as for understanding metabolic networks in complex and dynamic systems. One of the biggest challenges preventing more widespread adoption of these powerful techniques is that data analysis is difficult, especially when data sets are collected in high-throughput modes. Each technique presents its own challenges, requiring pipelines of (often poorly connected) tools for an end-to-end analysis, and a significant amount of manual analysis for steps where robust software is lacking. For individual steps within a workflow there exists commercial or free software at different stages of maturity, however there are few solutions that offer the capability for automated analysis from data collection through to statistical analysis. In the genomics and proteomics domains, the Galaxy framework has become a popular mechanism for building pipelines of modular tools (originally of command-line nature), through a web interface. Galaxy can be easily configured to run on single servers, compute clusters or cloud-based solutions. In this project our groups at the Universities of Liverpool and Birmingham, both of which have a track record in Galaxy development, will collaborate to build a set of metabolomics tools in Galaxy, enabling the construction of analysis pipelines for both NMR and MS analyses. Crucially, the pipelines will deliver data sets to a shared statistical analysis toolkit, enabling integrated analysis of data sets derived from both techniques. We will also contribute to the development of international data standards for metabolomics, and our new pipelines will facilitate the deposition of experimental metabolomics data into the MetaboLights database at the EBI.

Impact on health and society: The overall purpose of the project is to make data analysis for metabolomics more straightforward. Metabolomics is a technique increasingly used in human, animal and plant research, and as such, there is the potential for longer term (indirect) impacts, for example through facilitating biomarker discovery and the understanding of molecular mechanisms in fields including ageing, human and environmental health, food safety, industrial biotechnology, bioenergy and synthetic biology.

Economic impact: The facilitation of public data deposition has the potential for long term (indirect) economic impact, since it provides the opportunity for data sets (often collected at great expenses) to be re-purposed or re-analysed, fostering new research areas or in some cases reducing the requirement to collect new data.

Staff development: The postdocs involved will have the opportunity to work as part of an international network (for example working with the EBI, COSMOS, MSI and PSI) in a cutting edge software project. The PIs will benefit through exchange of skills and expertise between partners (the team has strong expertise in software engineering, MS, NMR, data analysis and statistics).