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.
Cite
CITATION STYLE
Battenberg, K., Kelly, S. T., Ras, R. A., Hetherington, N. A., Hayashi, M., & Minoda, A. (2022). A flexible cross-platform single-cell data processing pipeline. Nature Communications , 13(1). https://doi.org/10.1038/s41467-022-34681-z
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