scVMAP: a comprehensive platform for integrating single-cell chromatin accessibility regions with causal variants.

Integrating causal variant effects with single-cell assay for transposase-accessible chromatin with high-throughput sequencing (scATAC-seq) enables a more effective elucidation of the roles and impacts of genetic variations at the single-cell level. With the accumulation of genome-wide association studies and single-cell genomic data, there is an urgent need for comprehensive analysis and efficient exploration of these data to uncover the underlying biological processes. To address this, we developed scVMAP (https://bio.liclab.net/scvmap/), a user-friendly database aiming to provide trait-relevant cell populations at single-cell resolution. The current version of scVMAP has integrated 183 scATAC-seq datasets and 15 884 fine-mapping results, generating more than 32.1 billion trait-cell pairs, offering valuable resources for exploring the functional localization of single-cell variations. To enhance the understanding of how phenotypic associations are mapped to single-cell data, scVMAP provides a wealth of detailed information, including trait relevance scores (TRSs) for each cell, cell-type-specific differential gene and transcription factor (TF) activities, trait-relevant gene and TF interactions, and regulatory networks linking traits to cell types. Based on these comprehensive analytical results, scVMAP offers users convenient interfaces to search, browse, analyse, and visualize relationships between traits and cell populations at single-cell resolution.