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Software Options for the Analysis of MS-Proteomic Data

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Proteomics Data Analysis

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2361))

Abstract

Mass spectrometry (MS)-based proteomics is currently the most successful approach to measure and compare peptides and proteins in a large variety of biological samples. Modern mass spectrometers, equipped with high-resolution analyzers, provide large amounts of data output. This is the case of shotgun/bottom-up proteomics, which consists in the enzymatic digestion of protein into peptides that are then measured by MS-instruments through a data dependent acquisition (DDA) mode. Dedicated bioinformatic tools and platforms have been developed to face the increasing size and complexity of raw MS data that need to be processed and interpreted for large-scale protein identification and quantification. This chapter illustrates the most popular bioinformatics solution for the analysis of shotgun MS-proteomics data. A general description will be provided on the data preprocessing options and the different search engines available, including practical suggestions on how to optimize the parameters for peptide search, based on hands-on experience.

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Change history

  • 22 January 2022

    In the original version of this book, chapter 16 was published non-open access. It has now been changed to open access under a CC BY 4.0 license, and the copyright holder has been updated to “The Author(s).” This book has been updated with these changes.

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Funding

T.B.’s research activity is supported by grants from the Italian Association for Cancer Research (grant# IG-2018-21834) and by EPIC-XS, project number 823839, funded by the Horizon 2020 program of the European Union; F.M. is sponsored by a postdoctoral fellowship from FIEO-CCM.

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Author notes

  1. Avinash Yadav and Federica Marini contributed equally to this work.

Authors and Affiliations

  1. Department of Experimental Oncology, European Institute of Oncology (IEO), IRCCS, Milan, Italy

    Avinash Yadav, Federica Marini, Alessandro Cuomo & Tiziana Bonaldi

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  1. Avinash Yadav
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  2. Federica Marini
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  3. Alessandro Cuomo
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  4. Tiziana Bonaldi
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Correspondence to Tiziana Bonaldi .

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Editors and Affiliations

  1. Department of Biotechnology, University of Verona, VERONA, Verona, Italy

    Daniela Cecconi

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Yadav, A., Marini, F., Cuomo, A., Bonaldi, T. (2021). Software Options for the Analysis of MS-Proteomic Data. In: Cecconi, D. (eds) Proteomics Data Analysis. Methods in Molecular Biology, vol 2361. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1641-3_3

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  • DOI: https://doi.org/10.1007/978-1-0716-1641-3_3

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