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Integration of scATAC-Seq with scRNA-Seq Data

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Single Cell Transcriptomics

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2584))

Abstract

Single-cell studies are enabling our understanding of the molecular processes of normal cell development and the onset of several pathologies. For instance, single-cell RNA sequencing (scRNA-Seq) measures the transcriptome-wide gene expression at a single-cell resolution, allowing for studying the heterogeneity among the cells of the same population and revealing complex and rare cell populations. On the other hand, single-cell Assay for Transposase-Accessible Chromatin using sequencing (scATAC-Seq) can be used to define transcriptional and epigenetic changes by analyzing the chromatin accessibility at the single-cell level. However, the integration of multi-omics data still remains one of the most difficult tasks in bioinformatics. In this chapter, we focus on the combination of scRNA-Seq and scATACSeq data to perform an integrative analysis of the single-cell transcriptome and chromatin accessibility of human fetal progenitors.

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Author information

Authors and Affiliations

  1. Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany

    Ivan Berest

  2. Data Science, Pharma Research and Development, Roche Innovation Center Zurich, Zurich, Switzerland

    Ivan Berest

  3. Department of Human and Social Sciences, University of Bergamo, Bergamo, Italy

    Andrea Tangherloni

Authors
  1. Ivan Berest
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  2. Andrea Tangherloni
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Correspondence to Andrea Tangherloni .

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Editors and Affiliations

  1. Molecular Biotechnology Center, University of Torino, Torino, Italy

    Raffaele A. Calogero

  2. European Molecular Biology Laboratory, Heidelberg, Germany

    Vladimir Benes

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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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Berest, I., Tangherloni, A. (2023). Integration of scATAC-Seq with scRNA-Seq Data. In: Calogero, R.A., Benes, V. (eds) Single Cell Transcriptomics. Methods in Molecular Biology, vol 2584. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2756-3_15

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  • DOI: https://doi.org/10.1007/978-1-0716-2756-3_15

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-2755-6

  • Online ISBN: 978-1-0716-2756-3

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