scQTLbase: an int egr at ed human single-cell eQTL database

Abstract

Genome-wide association studies (GWAS) ha v e identified numerous genetic variants associated with diseases and traits. Ho w e v er, the functional interpretation of these variants remains challenging. Expression quantitative trait loci (eQTLs) have been widely used to identify mutations linked to disease, y et the y e xplain 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. Ho w e v er, 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 dat asets spanning 57 cell t ypes 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.