Database demonstrates comparative analysis of gene sets in cellular development and disease, highlighting aging and evolution factors.
Single-cell transcriptomics is reshaping the study of cellular physiology and pathology by revealing fine-grained cell functions and states. Interpreting these signals across cell types, organs, and species benefits from curated gene sets and tools for comparative analysis. Here, we introduce scGeneBank (http://8.142.154.29/scGeneBank or http://www.genebank.info), a database and analysis portal for gene set-driven exploration at single-cell resolution. The resource integrates 1134 carefully selected single-cell transcriptome datasets, totaling 104.9 million cells from 136 species and covering 430 organs and 1070 anatomical areas. It supports interactive analysis and visualization of 597 expert-curated gene sets organized into 28 biologically meaningful categories. Eight linked modules address common use cases: GeneSets (curated gene-set navigation), Species (dataset-level exploration), EvoScreening (cross-species comparisons within organs), OrganScreening (gene-set activity analysis across 35 human organs at cell-type resolution), StemAtlas (stemness profiling across species and organs), AgingScope (aging-related pathway analysis), PathoView (disease-associated gene expression analysis), and DeathMap (cell-death pathway activity visualization). Together, these modules provide a unified framework for comparing gene-set activity across species, organs, and cell types, enabling systematic studies of development, evolution, aging, disease, and cell death.
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Qin et al. (2025) studied this question.
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