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ShIVA: a user-friendly and interactive interface giving biologists control over their single-cell RNA-seq data
Single-cell technologies have revolutionised biological research and applications. As they continue to evolve with multi-omics and spatial resolution, analysing single-cell datasets is becoming increasingly complex. For biologists lacking expert data analysis resources, the problem is even more cruc...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10474127/ https://www.ncbi.nlm.nih.gov/pubmed/37658061 http://dx.doi.org/10.1038/s41598-023-40959-z |
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author | Aussel, Rudy Asif, Muhammad Chenag, Sabrina Jaeger, Sébastien Milpied, Pierre Spinelli, Lionel |
author_facet | Aussel, Rudy Asif, Muhammad Chenag, Sabrina Jaeger, Sébastien Milpied, Pierre Spinelli, Lionel |
author_sort | Aussel, Rudy |
collection | PubMed |
description | Single-cell technologies have revolutionised biological research and applications. As they continue to evolve with multi-omics and spatial resolution, analysing single-cell datasets is becoming increasingly complex. For biologists lacking expert data analysis resources, the problem is even more crucial, even for the simplest single-cell transcriptomics datasets. We propose ShIVA, an interface for the analysis of single-cell RNA-seq and CITE-seq data specifically dedicated to biologists. Intuitive, iterative and documented by video tutorials, ShIVA allows biologists to follow a robust and reproducible analysis process, mostly based on the Seurat v4 R package, to fully explore and quantify their dataset, to produce useful figures and tables and to export their work to allow more complex analyses performed by experts. |
format | Online Article Text |
id | pubmed-10474127 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-104741272023-09-03 ShIVA: a user-friendly and interactive interface giving biologists control over their single-cell RNA-seq data Aussel, Rudy Asif, Muhammad Chenag, Sabrina Jaeger, Sébastien Milpied, Pierre Spinelli, Lionel Sci Rep Article Single-cell technologies have revolutionised biological research and applications. As they continue to evolve with multi-omics and spatial resolution, analysing single-cell datasets is becoming increasingly complex. For biologists lacking expert data analysis resources, the problem is even more crucial, even for the simplest single-cell transcriptomics datasets. We propose ShIVA, an interface for the analysis of single-cell RNA-seq and CITE-seq data specifically dedicated to biologists. Intuitive, iterative and documented by video tutorials, ShIVA allows biologists to follow a robust and reproducible analysis process, mostly based on the Seurat v4 R package, to fully explore and quantify their dataset, to produce useful figures and tables and to export their work to allow more complex analyses performed by experts. Nature Publishing Group UK 2023-09-01 /pmc/articles/PMC10474127/ /pubmed/37658061 http://dx.doi.org/10.1038/s41598-023-40959-z Text en © The Author(s) 2023 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Aussel, Rudy Asif, Muhammad Chenag, Sabrina Jaeger, Sébastien Milpied, Pierre Spinelli, Lionel ShIVA: a user-friendly and interactive interface giving biologists control over their single-cell RNA-seq data |
title | ShIVA: a user-friendly and interactive interface giving biologists control over their single-cell RNA-seq data |
title_full | ShIVA: a user-friendly and interactive interface giving biologists control over their single-cell RNA-seq data |
title_fullStr | ShIVA: a user-friendly and interactive interface giving biologists control over their single-cell RNA-seq data |
title_full_unstemmed | ShIVA: a user-friendly and interactive interface giving biologists control over their single-cell RNA-seq data |
title_short | ShIVA: a user-friendly and interactive interface giving biologists control over their single-cell RNA-seq data |
title_sort | shiva: a user-friendly and interactive interface giving biologists control over their single-cell rna-seq data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10474127/ https://www.ncbi.nlm.nih.gov/pubmed/37658061 http://dx.doi.org/10.1038/s41598-023-40959-z |
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