Interpretation of T cell states from single-cell transcriptomics data using reference atlases.

Détails

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Etat: Public
Version: Final published version
Licence: CC BY 4.0
ID Serval
serval:BIB_BE1D257DF142
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Interpretation of T cell states from single-cell transcriptomics data using reference atlases.
Périodique
Nature communications
Auteur⸱e⸱s
Andreatta M., Corria-Osorio J., Müller S., Cubas R., Coukos G., Carmona S.J.
ISSN
2041-1723 (Electronic)
ISSN-L
2041-1723
Statut éditorial
Publié
Date de publication
20/05/2021
Peer-reviewed
Oui
Volume
12
Numéro
1
Pages
2965
Langue
anglais
Notes
Publication types: Journal Article ; Meta-Analysis ; Research Support, Non-U.S. Gov't
Publication Status: epublish
Résumé
Single-cell RNA sequencing (scRNA-seq) has revealed an unprecedented degree of immune cell diversity. However, consistent definition of cell subtypes and cell states across studies and diseases remains a major challenge. Here we generate reference T cell atlases for cancer and viral infection by multi-study integration, and develop ProjecTILs, an algorithm for reference atlas projection. In contrast to other methods, ProjecTILs allows not only accurate embedding of new scRNA-seq data into a reference without altering its structure, but also characterizing previously unknown cell states that "deviate" from the reference. ProjecTILs accurately predicts the effects of cell perturbations and identifies gene programs that are altered in different conditions and tissues. A meta-analysis of tumor-infiltrating T cells from several cohorts reveals a strong conservation of T cell subtypes between human and mouse, providing a consistent basis to describe T cell heterogeneity across studies, diseases, and species.
Mots-clé
Animals, Cell Differentiation/immunology, Cohort Studies, Disease Models, Animal, Gene Expression Regulation/immunology, Humans, Lymphocytes, Tumor-Infiltrating/immunology, Mice, Neoplasms/blood, Neoplasms/immunology, Neoplasms/pathology, RNA-Seq/methods, Reference Values, Single-Cell Analysis/methods, Software, Species Specificity, T-Lymphocyte Subsets/immunology, T-Lymphocytes/immunology, Tumor Microenvironment/immunology, Virus Diseases/blood, Virus Diseases/immunology
Pubmed
Web of science
Open Access
Oui
Financement(s)
Fonds national suisse / 180010
Création de la notice
26/05/2021 18:12
Dernière modification de la notice
12/01/2022 7:13
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