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A flexible cross-platform single-cell data processing pipeline.

Kai BattenbergS Thomas KellyRadu Abu RasNicola A HetheringtonMakoto HayashiAki Minoda
Published in: Nature communications (2022)
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.
Keyphrases
  • single cell
  • rna seq
  • high throughput
  • electronic health record
  • big data
  • data analysis
  • healthcare
  • cell proliferation
  • signaling pathway
  • endoplasmic reticulum stress
  • single molecule