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Normalization of Single-Cell RNA-Seq Data

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RNA Bioinformatics

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2284))

Abstract

Normalization is an important step in the analysis of single-cell RNA-seq data. While no single method outperforms all others in all datasets, the choice of normalization can have profound impact on the results. Data-driven metrics can be used to rank normalization methods and select the best performers. Here, we show how to use R/Bioconductor to calculate normalization factors, apply them to compute normalized data, and compare several normalization approaches. Finally, we briefly show how to perform downstream analysis steps on the normalized data.

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Authors and Affiliations

  1. Department of Statistical Sciences, University of Padova, Padova, Italy

    Davide Risso

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  1. Davide Risso
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Correspondence to Davide Risso .

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Editors and Affiliations

  1. Dipartimento Di Bioscienze Biotecnologie E Biofarmaceutica, Università degli Studi di Bari Aldo Moro, Bari, Italy

    Ernesto Picardi

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Risso, D. (2021). Normalization of Single-Cell RNA-Seq Data. In: Picardi, E. (eds) RNA Bioinformatics. Methods in Molecular Biology, vol 2284. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1307-8_17

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  • DOI: https://doi.org/10.1007/978-1-0716-1307-8_17

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-1306-1

  • Online ISBN: 978-1-0716-1307-8

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