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

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.