Multimodal hierarchical classification of CITE-seq data delineates immune cell states across lineages and tissues

Single-cell RNA sequencing (scRNA-seq) is invaluable for profiling cellular heterogeneity and transcriptional states, but transcriptomic profiles do not always delineate subsets defined by surface proteins. Cellular indexing of transcriptomes and epitopes (CITE-seq) enables simultaneous profiling of...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Cell reports methods 2025-01, Vol.5 (1), p.100938, Article 100938
Hauptverfasser:	Caron, Daniel P., Specht, William L., Chen, David, Wells, Steven B., Szabo, Peter A., Jensen, Isaac J., Farber, Donna L., Sims, Peter A.
Format:	Artikel
Sprache:	eng
Schlagworte:	batch integration Cell Lineage - genetics CITE-seq Gene Expression Profiling - methods human immunology Humans immune cells machine learning memory T cells multimodal sequencing Sequence Analysis, RNA - methods Single-Cell Analysis - methods single-cell classification single-cell sequencing spatial profiling T-Lymphocyte Subsets - classification T-Lymphocyte Subsets - immunology T-Lymphocyte Subsets - metabolism Transcriptome
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!