Back to Search Start Over

scLiverDB: a Database of Human and Mouse Liver Transcriptome Landscapes at Single‐Cell Resolution.

Authors :
Pan, Qi
Li, Borui
Lin, Dong
Miao, Ya‐Ru
Luo, Tao
Yue, Tao
Luo, Qingming
Guo, An‐Yuan
Zhang, Zhihong
Source :
Small Methods. Sep2023, Vol. 7 Issue 9, p1-11. 11p.
Publication Year :
2023

Abstract

The liver is critical for the digestive and immune systems. Although the physiology and pathology of liver have been well studied and many scRNA‐seq data are generated, a database and landscape for characterizing cell types and gene expression in different liver diseases or developmental stages at single‐cell resolution are lacking. Hence, scLiverDB is developed, a specialized database for human and mouse liver transcriptomes to unravel the landscape of liver cell types, cell heterogeneity and gene expression at single‐cell resolution across various liver diseases/cell types/developmental stages. To date, 62 datasets including 9,050 samples and 1,741,734 cells is curated. A uniform workflow is used, which included quality control, dimensional reduction, clustering, and cell‐type annotation to analyze datasets on the same platform; integrated manual and automatic methods for accurate cell‐type identification and provided a user‐friendly web interface with multiscale functions. There are two case studies to show the usefulness of scLiverDB, which identified the LTB (lymphotoxin Beta) gene as a potential biomarker of lymphoid cells differentiation and showed the expression changes of Foxa3 (forkhead box A3) in liver chronic progressive diseases. This work provides a crucial resource to resolve molecular and cellular information in normal, diseased, and developing human and mouse livers. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
23669608
Volume :
7
Issue :
9
Database :
Academic Search Index
Journal :
Small Methods
Publication Type :
Academic Journal
Accession number :
172046485
Full Text :
https://doi.org/10.1002/smtd.202201421