scQTLbase

scQTLbase integrates human single-cell expression quantitative trait loci (sc-eQTL) data to map SNP–gene associations across 304 datasets, 57 cell types and 95 cell states and to support interpretation of GWAS variants.

Key Features:

• Comprehensive database: Aggregates sc-eQTL data from 304 datasets spanning 57 cell types and 95 cell states.
• Extensive SNP associations: Includes approximately 16 million SNPs that are significantly associated with gene expression in specific cell types or states.
• Disease-associated sc-eQTLs: Contains around 0.69 million disease-associated sc-eQTLs linked to 3,333 traits or diseases.
• sc-eQTL search: Provides search functionality to retrieve specific single-cell eQTLs.
• Gene expression visualization (UMAP): Visualizes gene expression at single-cell resolution using UMAP plots.
• Genome browser and colocalization visualization: Supports genomic context exploration and visualization of colocalizations between sc-eQTLs and GWAS datasets.

Scientific Applications:

• Prioritization of disease susceptibility genes: Links SNPs to cell-type-specific expression to prioritize candidate susceptibility and novel risk genes.
• Interpretation of GWAS loci: Facilitates colocalization analyses between sc-eQTLs and GWAS signals to interpret genetic associations.
• Study of transcriptional regulation: Enables analysis of genetic effects on transcriptional regulation at single-cell resolution across cell types and states.
• Characterization of cellular heterogeneity: Supports investigation of cell-state-specific genetic regulation in health and disease.

Methodology:

Integration of numerous single-cell RNA-seq datasets to identify and compile single-cell eQTLs across 57 cell types and 95 cell states, producing aggregated SNP–gene association sets and disease-linked sc-eQTL annotations.