Meta-analysis of single-cell and single-nucleus transcriptomics reveals kidney cell type consensus signatures

While the amount of studies involving single-cell or single-nucleus RNA-sequencing technologies grows exponentially within the biomedical research area, the kidney field requires reference transcriptomic signatures to allocate each cluster its matching cell type. The present meta-analysis of 39 prev...

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Autores principales: Quatredeniers, Marceau, Serafin, Alice S., Benmerah, Alexandre, Rausell, Antonio, Saunier, Sophie, Viau, Amandine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Analysis
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10244446/
https://www.ncbi.nlm.nih.gov/pubmed/37280226
http://dx.doi.org/10.1038/s41597-023-02209-9
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author Quatredeniers, Marceau
Serafin, Alice S.
Benmerah, Alexandre
Rausell, Antonio
Saunier, Sophie
Viau, Amandine
author_facet Quatredeniers, Marceau
Serafin, Alice S.
Benmerah, Alexandre
Rausell, Antonio
Saunier, Sophie
Viau, Amandine
author_sort Quatredeniers, Marceau
collection PubMed
description While the amount of studies involving single-cell or single-nucleus RNA-sequencing technologies grows exponentially within the biomedical research area, the kidney field requires reference transcriptomic signatures to allocate each cluster its matching cell type. The present meta-analysis of 39 previously published datasets, from 7 independent studies, involving healthy human adult kidney samples, offers a set of 24 distinct consensus kidney cell type signatures. The use of these signatures may help to assure the reliability of cell type identification in future studies involving single-cell and single-nucleus transcriptomics while improving the reproducibility in cell type allocation.
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spelling pubmed-102444462023-06-08 Meta-analysis of single-cell and single-nucleus transcriptomics reveals kidney cell type consensus signatures Quatredeniers, Marceau Serafin, Alice S. Benmerah, Alexandre Rausell, Antonio Saunier, Sophie Viau, Amandine Sci Data Analysis While the amount of studies involving single-cell or single-nucleus RNA-sequencing technologies grows exponentially within the biomedical research area, the kidney field requires reference transcriptomic signatures to allocate each cluster its matching cell type. The present meta-analysis of 39 previously published datasets, from 7 independent studies, involving healthy human adult kidney samples, offers a set of 24 distinct consensus kidney cell type signatures. The use of these signatures may help to assure the reliability of cell type identification in future studies involving single-cell and single-nucleus transcriptomics while improving the reproducibility in cell type allocation. Nature Publishing Group UK 2023-06-06 /pmc/articles/PMC10244446/ /pubmed/37280226 http://dx.doi.org/10.1038/s41597-023-02209-9 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 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 Analysis
Quatredeniers, Marceau
Serafin, Alice S.
Benmerah, Alexandre
Rausell, Antonio
Saunier, Sophie
Viau, Amandine
Meta-analysis of single-cell and single-nucleus transcriptomics reveals kidney cell type consensus signatures
title Meta-analysis of single-cell and single-nucleus transcriptomics reveals kidney cell type consensus signatures
title_full Meta-analysis of single-cell and single-nucleus transcriptomics reveals kidney cell type consensus signatures
title_fullStr Meta-analysis of single-cell and single-nucleus transcriptomics reveals kidney cell type consensus signatures
title_full_unstemmed Meta-analysis of single-cell and single-nucleus transcriptomics reveals kidney cell type consensus signatures
title_short Meta-analysis of single-cell and single-nucleus transcriptomics reveals kidney cell type consensus signatures
title_sort meta-analysis of single-cell and single-nucleus transcriptomics reveals kidney cell type consensus signatures
topic Analysis
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10244446/
https://www.ncbi.nlm.nih.gov/pubmed/37280226
http://dx.doi.org/10.1038/s41597-023-02209-9
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