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Single Cell Transcriptomics pp 311–335Cite as

Using “Galaxy-rCASC”: A Public Galaxy Instance for Single-Cell RNA-Seq Data Analysis

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

Abstract

rCASC is a modular workflow providing an integrated environment for single-cell RNA-seq (scRNA-Seq) data analysis exploiting Docker containers to achieve functional and computational reproducibility. It was initially developed as an R package usable also through a Java GUI. However, the Java frontend cannot be employed when running rCASC on a remote server, a typical setup due to the significant computational resources commonly needed to analyze scRNA-Seq data.

To allow the use of rCASC through a graphical user interface on the client side and to harness the many advantages provided by the Galaxy platform, we have made rCASC available as a Galaxy set of tools, also providing a dedicated public instance of Galaxy named “Galaxy-rCASC.” To integrate rCASC into Galaxy, all its functions, originally implemented as a set of Docker containers to maximize reproducibility, have been extensively reworked to become independent from the R package functions that launch them in the original implementation. Furthermore, suitable Galaxy wrappers have been developed for most functions of rCASC. We provide a detailed reference document to the use of Galaxy-rCASC with insights and explanations on the platform functionalities, parameters, and output while guiding the reader through the typical rCASC analysis workflow of a scRNA-Seq dataset.

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Author information

Authors and Affiliations

  1. Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, National Research Council (CNR), Bari, Italy

    Pietro Mandreoli, Marco Antonio Tangaro & Federico Zambelli

  2. Molecular Biotechnology Center, Turin, Turin, Italy

    Luca Alessandri

  3. Department of Biosciences, University of Milan, Milan, Italy

    Pietro Mandreoli & Federico Zambelli

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

    Raffaele A. Calogero

Authors
  1. Pietro Mandreoli
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  2. Luca Alessandri
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  3. Raffaele A. Calogero
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  4. Marco Antonio Tangaro
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  5. Federico Zambelli
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Corresponding author

Correspondence to Federico Zambelli .

Editor information

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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Mandreoli, P., Alessandri, L., Calogero, R.A., Tangaro, M.A., Zambelli, F. (2023). Using “Galaxy-rCASC”: A Public Galaxy Instance for Single-Cell RNA-Seq Data Analysis. 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_16

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  • DOI: https://doi.org/10.1007/978-1-0716-2756-3_16

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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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