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. 2023:2584:311-335.
doi: 10.1007/978-1-0716-2756-3_16.

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

Pietro Mandreoli  1   2 , Luca Alessandri  3 , Raffaele A Calogero  4 , Marco Antonio Tangaro  1 , Federico Zambelli  5   6
Affiliations

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

Pietro Mandreoli et al. Methods Mol Biol. 2023.

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.

Keywords: Docker; Galaxy; Reproducibility; scRNA-Seq.

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