MiMIR: R-shiny application to infer risk factors and endpoints from Nightingale 
Health's 1H-NMR Metabolomics data

Bizzarri, D.; Reinders, M. J. T.; Beekman, M.; Slagboom, P. E.; van den Akker, E. B.

doi:10.1093/bioinformatics/btac388

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MiMIR: R-shiny application to infer risk factors and endpoints from Nightingale Health's 1H-NMR Metabolomics data

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Slagboom, P. E.
Slagboom – Molecular Epidemiology, External and Associated Groups, Max Planck Institute for Biology of Ageing, Max Planck Society;

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https://www.ncbi.nlm.nih.gov/pubmed/35695757
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Citation

Bizzarri, D., Reinders, M. J. T., Beekman, M., Slagboom, P. E., & van den Akker, E. B. (2022). MiMIR: R-shiny application to infer risk factors and endpoints from Nightingale Health's 1H-NMR Metabolomics data. Bioinformatics. doi:10.1093/bioinformatics/btac388.

Cite as: https://hdl.handle.net/21.11116/0000-000B-BB13-D

Abstract

MOTIVATION: 1H-NMR metabolomics is rapidly becoming a standard resource in large epidemiological studies to acquire metabolic profiles in large numbers of samples in a relatively low-priced and standardized manner. Concomitantly, metabolomics-based models are increasingly developed that capture disease risk or clinical risk factors. These developments raise the need for user-friendly toolbox to inspect new 1H-NMR metabolomics data and project a wide array of previously established risk models. RESULTS: We present MiMIR (Metabolomics-based Models for Imputing Risk), a graphical user interface that provides an intuitive framework for ad-hoc statistical analysis of Nightingale Health's 1H-NMR metabolomics data and allows for the projection and calibration of 24 pre-trained metabolomics-based models, without any pre-required programming knowledge. AVAILABILITY: The R-shiny package is available in CRAN or downloadable at https://github.com/DanieleBizzarri/MiMIR, together with an extensive user manual (also available as Supplementary Documents to the paper). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.