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Sequences to Differences in Gene Expression: Analysis of RNA-Seq Data

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Cancer Cell Biology

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2508))

Abstract

RNA-Seq is now a routinely employed assay to measure gene expression. As the technique matured over the last decade, so have dedicated analytic tools. In this chapter, we first describe the mainstream as well as the most up-to-date protocols and their implications on downstream analysis. We then detail the steps entailing RNA-Seq analysis in three main stages: (i) preprocessing and data preparation, (ii) upstream processing, and (iii) high-level analyses. We review the most recent and relevant tools as one workflow following a stepwise order. The chapter further encompasses in-depth features of these tools. Details of the required code are made available throughout the chapter, as well as of the underlying statistics. We illustrate these steps with analysis of publicly available RNA-Seq data.

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Acknowledgment

This work was supported by the Max Planck Society and the German Cancer Research Centre (DKFZ).

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Authors and Affiliations

  1. Moscow Institute of Physics and Technology, Dolgoprudny, Russia

    Polina V. Pavlovich

  2. Universitätskilinkum Freiburg, Freiburg, Germany

    Pierre Cauchy

  3. Max Planck Institute of Immunobiology and Epigenetics, Freiburg, Germany

    Pierre Cauchy

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  1. Polina V. Pavlovich
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  2. Pierre Cauchy
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Correspondence to Pierre Cauchy .

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Editors and Affiliations

  1. Department of Biochemistry, Memorial University of Newfoundland, St. John's, NL, Canada

    Sherri L. Christian

1 Electronic Supplementary Material

Annex 1

Bash code for upstream processing (DOCX 27 kb)

Annex 2

R code for downstream analyses (DOCX 23 kb)

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Pavlovich, P.V., Cauchy, P. (2022). Sequences to Differences in Gene Expression: Analysis of RNA-Seq Data. In: Christian, S.L. (eds) Cancer Cell Biology. Methods in Molecular Biology, vol 2508. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2376-3_20

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  • DOI: https://doi.org/10.1007/978-1-0716-2376-3_20

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