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Analysis of Single-Cell RNA-seq Data

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Statistical Genomics

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2629))

Abstract

As single-cell RNA sequencing experiments continue to advance scientific discoveries across biological disciplines, an increasing number of analysis tools and workflows for analyzing the data have been developed. In this chapter, we describe a standard workflow and elaborate on relevant data analysis tools for analyzing single-cell RNA sequencing data. We provide recommendations for the appropriate use of commonly used methods, with code examples and analysis interpretations.

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Author information

Authors and Affiliations

  1. Department of Biostatistics, University of Florida, Gainesville, Florida, USA

    Xiaoru Dong & Rhonda Bacher

Authors
  1. Xiaoru Dong
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  2. Rhonda Bacher
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Corresponding author

Correspondence to Rhonda Bacher .

Editor information

Editors and Affiliations

  1. Moffitt Cancer Center, Tampa, FL, USA

    Brooke Fridley

  2. Department of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, USA

    Xuefeng Wang

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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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Dong, X., Bacher, R. (2023). Analysis of Single-Cell RNA-seq Data. In: Fridley, B., Wang, X. (eds) Statistical Genomics. Methods in Molecular Biology, vol 2629. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2986-4_6

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  • DOI: https://doi.org/10.1007/978-1-0716-2986-4_6

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-2985-7

  • Online ISBN: 978-1-0716-2986-4

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