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A flexible cross-platform single-cell data processing pipeline
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 sup...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9652453/ https://www.ncbi.nlm.nih.gov/pubmed/36369450 http://dx.doi.org/10.1038/s41467-022-34681-z |
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author | Battenberg, Kai Kelly, S. Thomas Ras, Radu Abu Hetherington, Nicola A. Hayashi, Makoto Minoda, Aki |
author_facet | Battenberg, Kai Kelly, S. Thomas Ras, Radu Abu Hetherington, Nicola A. Hayashi, Makoto Minoda, Aki |
author_sort | Battenberg, Kai |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9652453 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-96524532022-11-15 A flexible cross-platform single-cell data processing pipeline Battenberg, Kai Kelly, S. Thomas Ras, Radu Abu Hetherington, Nicola A. Hayashi, Makoto Minoda, Aki Nat Commun Article 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. Nature Publishing Group UK 2022-11-11 /pmc/articles/PMC9652453/ /pubmed/36369450 http://dx.doi.org/10.1038/s41467-022-34681-z Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Battenberg, Kai Kelly, S. Thomas Ras, Radu Abu Hetherington, Nicola A. Hayashi, Makoto Minoda, Aki A flexible cross-platform single-cell data processing pipeline |
title | A flexible cross-platform single-cell data processing pipeline |
title_full | A flexible cross-platform single-cell data processing pipeline |
title_fullStr | A flexible cross-platform single-cell data processing pipeline |
title_full_unstemmed | A flexible cross-platform single-cell data processing pipeline |
title_short | A flexible cross-platform single-cell data processing pipeline |
title_sort | flexible cross-platform single-cell data processing pipeline |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9652453/ https://www.ncbi.nlm.nih.gov/pubmed/36369450 http://dx.doi.org/10.1038/s41467-022-34681-z |
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