scMOVIR: a single-cell multi-omics database for human viral infections and immune responses

Abstract

Viral infections impose a substantial threat to human health, characterized by a wide range of pathogens, clinical manifestations, and complex immune responses. Single-cell multi-omics technologies have revolutionized the study of antiviral immunity by resolving cellular heterogeneity, transcriptional reprogramming, and clonal dynamics. However, no resource has yet comprehensively integrated such datasets in the context of viral infections. Here, we present scMOVIR, a single-cell multi-omics database for human viral infections and immune responses. The database systematically integrates transcriptomic, proteomic, and immune receptor repertoire profiles at single-cell resolution, compiling 8532 human samples across 114 viral species, subtypes, and strains. These datasets span 59 well-defined disease states, including acute and chronic infections, virus-associated malignancies, and immune-related disorders, and extend across >30 tissue types. In addition, these datasets incorporate vaccination cohorts, therapeutic interventions, and time-course models of infection. To ensure consistency and interoperability, all datasets undergo standardized preprocessing, including batch correction and unified cell-type annotation, with metadata harmonized using authoritative ontologies. scMOVIR provides user-friendly interfaces for dataset exploration and interactive visualization of cellular dynamics and molecular profiles, offering a high-resolution reference for investigating virus-host immune interactions and supporting antiviral research. The database is freely accessible at https://pgx.zju.edu.cn/scmovir.