Single nucleus transcriptomics data integration recapitulates the major cell types in human liver.
Hepatol Res
; 51(2): 233-238, 2021 Feb.
Article
en En
| MEDLINE
| ID: mdl-33119937
ABSTRACT
AIM:
The aim of this study was to explore the benefits of data integration from different platforms for single nucleus transcriptomics profiling to characterize cell populations in human liver.METHODS:
We generated single-nucleus RNA sequencing data from Chromium 10X Genomics and Drop-seq for a human liver sample. We utilized state of the art bioinformatics tools to undertake a rigorous quality control and to integrate the data into a common space summarizing the gene expression variation from the respective platforms, while accounting for known and unknown confounding factors.RESULTS:
Analysis of single nuclei transcriptomes from both 10X and Drop-seq allowed identification of the major liver cell types, while the integrated set obtained enough statistical power to separate a small population of inactive hepatic stellate cells that was not characterized in either of the platforms.CONCLUSIONS:
Integration of droplet-based single nucleus transcriptomics data enabled identification of a small cluster of inactive hepatic stellate cells that highlights the potential of our approach. We suggest single-nucleus RNA sequencing integrative approaches could be utilized to design larger and cost-effective studies.
Texto completo:
1
Bases de datos:
MEDLINE
Tipo de estudio:
Prognostic_studies
Idioma:
En
Revista:
Hepatol Res
Año:
2021
Tipo del documento:
Article
País de afiliación:
Suecia