PLAE web app enables powerful searching and multiple visualizations across one million unified single-cell ocular transcriptomes

PURPOSETo create a high performance reactive web application to query single cell gene expression data across cell type, species, study, and other factors. METHODSWe updated the content and structure of the underlying data (single cell Eye in a Disk, scEiaD) and wrote the web application PLAE (https://plae.nei.nih.gov) to visualize and explore it. RESULTSThe new portal provides quick visualization of over a million individual cells from vertebrate eye-and body transcriptomes encomopassing four species, 60 cell types, six ocular tissues, and 23 body tissues across 37 publications. To demonstrate the value of this unified pan-eye dataset, we replicate known neurogenic and cone macula markers as well as propose six new cone human region markers. CONCLUSIONThe PLAE web application provides the eye community a powerful and quick means to test hypotheses related to gene expression across a highly diverse, community-derived database.