Meta-analysis of single-cell and single-nucleus transcriptomics reveals kidney cell type consensus signatures.
Journal
Scientific data
ISSN: 2052-4463
Titre abrégé: Sci Data
Pays: England
ID NLM: 101640192
Informations de publication
Date de publication:
06 06 2023
06 06 2023
Historique:
received:
29
07
2022
accepted:
05
05
2023
medline:
8
6
2023
pubmed:
7
6
2023
entrez:
6
6
2023
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 37280226
doi: 10.1038/s41597-023-02209-9
pii: 10.1038/s41597-023-02209-9
pmc: PMC10244446
doi:
Types de publication
Meta-Analysis
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
361Subventions
Organisme : Agence Nationale de la Recherche (French National Research Agency)
ID : ANR-17-RHUS-0002
Organisme : Agence Nationale de la Recherche (French National Research Agency)
ID : ANR-17-RHUS-0002
Organisme : Agence Nationale de la Recherche (French National Research Agency)
ID : ANR-17-RHUS-0002
Informations de copyright
© 2023. The Author(s).
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