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Integrating Multiple Quantitative Proteomic Analyses Using MetaMSD

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Statistical Analysis of Proteomic Data

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2426))

Abstract

MetaMSD is a proteomic software that integrates multiple quantitative mass spectrometry data analysis results using statistical summary combination approaches. By utilizing this software, scientists can combine results from their pilot and main studies to maximize their biomarker discovery while effectively controlling false discovery rates. It also works for combining proteomic datasets generated by different labeling techniques and/or different types of mass spectrometry instruments. With these advantages, MetaMSD enables biological researchers to explore various proteomic datasets in public repositories to discover new biomarkers and generate interesting hypotheses for future studies. In this protocol, we provide a step-by-step procedure on how to install and perform a meta-analysis for quantitative proteomics using MetaMSD.

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Acknowledgements

MetaMSD software development was supported by grants from the National Institute of General Medical Sciences (GM103440 and 1R15GM126562-01).

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Authors and Affiliations

  1. School of Public Health, University of Nevada Reno, Reno, NV, USA

    So Young Ryu & Sujung Kim

  2. Department of Psychology Institute for Neuroscience, University of Nevada Reno, Reno, NV, USA

    Miriam P. Yun

Authors
  1. So Young Ryu
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  2. Miriam P. Yun
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  3. Sujung Kim
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Corresponding author

Correspondence to So Young Ryu .

Editor information

Editors and Affiliations

  1. Exploring the Dynamics of Proteomes, Proteomics French Infrastructure, Université Grenoble Alpes, CNRS, CEA, INSERM, Grenoble, France

    Thomas Burger

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© 2023 The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature

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Ryu, S.Y., Yun, M.P., Kim, S. (2023). Integrating Multiple Quantitative Proteomic Analyses Using MetaMSD. In: Burger, T. (eds) Statistical Analysis of Proteomic Data. Methods in Molecular Biology, vol 2426. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1967-4_16

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  • DOI: https://doi.org/10.1007/978-1-0716-1967-4_16

  • Published:

  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-1966-7

  • Online ISBN: 978-1-0716-1967-4

  • eBook Packages: Springer Protocols

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