Genome-wide association studies (GWAS) have identified numerous genetic variants associated with diseases and traits. However, the functional interpretation of these variants remains challenging. Expression quantitative trait loci (eQTLs) have been widely used to identify mutations linked to disease, yet they explain only 20-50% of disease-related variants. Single-cell eQTLs (sc-eQTLs) studies provide an immense opportunity to identify new disease risk genes with expanded eQTL scales and transcriptional regulation at a much finer resolution. However, there is no comprehensive database dedicated to single-cell eQTLs that users can use to search, analyse and visualize them. Therefore, we developed the scQTLbase (http://bioinfo.szbl.ac.cn/scQTLbase), the first integrated human sc-eQTLs portal, featuring 304 datasets spanning 57 cell types and 95 cell states. It contains ∼16 million SNPs significantly associated with cell-type/state gene expression and ∼0.69 million disease-associated sc-eQTLs from 3 333 traits/diseases. In addition, scQTLbase offers sc-eQTL search, gene expression visualization in UMAP plots, a genome browser, and colocalization visualization based on the GWAS dataset of interest. scQTLbase provides a one-stop portal for sc-eQTLs that will significantly advance the discovery of disease susceptibility genes.
