Single-cell RNA sequencing has rapidly expanded the scale of skin transcriptomic data, yet these datasets remain fragmented across studies spanning different species, diseases and experimental manipulations. An up-to-date, comprehensive, and queryable single-cell cross-species repository for skin is still lacking. Here, we present scSAID (skin-scsaid.com), a single-cell database with an interactive web portal offering a broad suite of in-depth analyses for human and mouse skin. It integrates more than 1.2 million high-quality cells collected from 252 samples, establishing a unified reference for cell-type annotation, cross-species comparison and pathological studies. Using psoriasis as a case study, we demonstrate how scSAID can be used to evaluate how faithfully mouse models reproduce human pathology. Systematic comparison with the imiquimod-induced mouse model revealed numerous species-specific molecular signatures of psoriasis, including human-specific NFKB1 activation and STAT1 involvement, indicating that the current mouse model captures only limited aspects of the disease. We further introduce psoSpotter, a disease-biomarker-selection algorithm that, coupled with in silico perturbation using scSAID data, uncovers PPIA as a novel psoriasis drug target, illustrating the potential of scSAID for identifying therapeutic approaches. Overall, scSAID delivers a large-scale, cross-species skin single-cell resource and analysis platform, opening new opportunities for the discovery of disease-relevant targets in skin diseases.
