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Processing single-cell RNA-seq data for dimension reduction-based analyses using open-source tools
Single-cell RNA sequencing data require several processing procedures to arrive at interpretable results. While commercial platforms can serve as “one-stop shops” for data analysis, they relinquish the flexibility required for customized analyses and are often inflexible between experimental systems...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8082116/ https://www.ncbi.nlm.nih.gov/pubmed/33982010 http://dx.doi.org/10.1016/j.xpro.2021.100450 |
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author | Chen, Bob Ramirez-Solano, Marisol A. Heiser, Cody N. Liu, Qi Lau, Ken S. |
author_facet | Chen, Bob Ramirez-Solano, Marisol A. Heiser, Cody N. Liu, Qi Lau, Ken S. |
author_sort | Chen, Bob |
collection | PubMed |
description | Single-cell RNA sequencing data require several processing procedures to arrive at interpretable results. While commercial platforms can serve as “one-stop shops” for data analysis, they relinquish the flexibility required for customized analyses and are often inflexible between experimental systems. For instance, there is no universal solution for the discrimination of informative or uninformative encapsulated cellular material; thus, pipeline flexibility takes priority. Here, we demonstrate a full data analysis pipeline, constructed modularly from open-source software, including tools that we have contributed. For complete details on the use and execution of this protocol, please refer to Petukhov et al. (2018), Heiser et al. (2020), and Heiser and Lau (2020). |
format | Online Article Text |
id | pubmed-8082116 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-80821162021-05-11 Processing single-cell RNA-seq data for dimension reduction-based analyses using open-source tools Chen, Bob Ramirez-Solano, Marisol A. Heiser, Cody N. Liu, Qi Lau, Ken S. STAR Protoc Protocol Single-cell RNA sequencing data require several processing procedures to arrive at interpretable results. While commercial platforms can serve as “one-stop shops” for data analysis, they relinquish the flexibility required for customized analyses and are often inflexible between experimental systems. For instance, there is no universal solution for the discrimination of informative or uninformative encapsulated cellular material; thus, pipeline flexibility takes priority. Here, we demonstrate a full data analysis pipeline, constructed modularly from open-source software, including tools that we have contributed. For complete details on the use and execution of this protocol, please refer to Petukhov et al. (2018), Heiser et al. (2020), and Heiser and Lau (2020). Elsevier 2021-04-17 /pmc/articles/PMC8082116/ /pubmed/33982010 http://dx.doi.org/10.1016/j.xpro.2021.100450 Text en © 2021 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Protocol Chen, Bob Ramirez-Solano, Marisol A. Heiser, Cody N. Liu, Qi Lau, Ken S. Processing single-cell RNA-seq data for dimension reduction-based analyses using open-source tools |
title | Processing single-cell RNA-seq data for dimension reduction-based analyses using open-source tools |
title_full | Processing single-cell RNA-seq data for dimension reduction-based analyses using open-source tools |
title_fullStr | Processing single-cell RNA-seq data for dimension reduction-based analyses using open-source tools |
title_full_unstemmed | Processing single-cell RNA-seq data for dimension reduction-based analyses using open-source tools |
title_short | Processing single-cell RNA-seq data for dimension reduction-based analyses using open-source tools |
title_sort | processing single-cell rna-seq data for dimension reduction-based analyses using open-source tools |
topic | Protocol |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8082116/ https://www.ncbi.nlm.nih.gov/pubmed/33982010 http://dx.doi.org/10.1016/j.xpro.2021.100450 |
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