A flexible cross-platform single-cell data processing pipeline

Kai Battenberg, S. Thomas Kelly, Radu Abu Ras, Nicola A. Hetherington, Makoto Hayashi and Aki Minoda ()
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Kai Battenberg: Center for Integrative Medical Sciences, RIKEN
S. Thomas Kelly: Center for Integrative Medical Sciences, RIKEN
Radu Abu Ras: Center for Integrative Medical Sciences, RIKEN
Nicola A. Hetherington: Radboud University
Makoto Hayashi: Center for Sustainable Resource Science, RIKEN
Aki Minoda: Center for Integrative Medical Sciences, RIKEN

Nature Communications, 2022, vol. 13, issue 1, 1-7

Abstract: Abstract Single-cell RNA-sequencing analysis to quantify the RNA molecules in individual cells has become popular, as it can obtain a large amount of information from each experiment. We introduce UniverSC ( https://github.com/minoda-lab/universc ), a universal single-cell RNA-seq data processing tool that supports any unique molecular identifier-based platform. Our command-line tool, docker image, and containerised graphical application enables consistent and comprehensive integration, comparison, and evaluation across data generated from a wide range of platforms. We also provide a cross-platform application to run UniverSC via a graphical user interface, available for macOS, Windows, and Linux Ubuntu, negating one of the bottlenecks with single-cell RNA-seq analysis that is data processing for researchers who are not bioinformatically proficient.

Date: 2022
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DOI: 10.1038/s41467-022-34681-z

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