Single-cell sequencing analysis within biologically relevant dimensions.
Cell Syst
; 15(1): 83-103.e11, 2024 01 17.
Article
en En
| MEDLINE
| ID: mdl-38198894
ABSTRACT
The currently predominant approach to transcriptomic and epigenomic single-cell analysis depends on a rigid perspective constrained by reduced dimensions and algorithmically derived and annotated clusters. Here, we developed Seqtometry (sequencing-to-measurement), a single-cell analytical strategy based on biologically relevant dimensions enabled by advanced scoring with multiple gene sets (signatures) for examination of gene expression and accessibility across various organ systems. By utilizing information only in the form of specific signatures, Seqtometry bypasses unsupervised clustering and individual annotations of clusters. Instead, Seqtometry combines qualitative and quantitative cell-type identification with specific characterization of diverse biological processes under experimental or disease conditions. Comprehensive analysis by Seqtometry of various immune cells as well as other cells from different organs and disease-induced states, including multiple myeloma and Alzheimer's disease, surpasses corresponding cluster-based analytical output. We propose Seqtometry as a single-cell sequencing analysis approach applicable for both basic and clinical research.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Perfilación de la Expresión Génica
/
Transcriptoma
Tipo de estudio:
Prognostic_studies
/
Qualitative_research
Idioma:
En
Revista:
Cell Syst
Año:
2024
Tipo del documento:
Article
País de afiliación:
Estados Unidos