Purpose: To create a high-performance reactive web application to query single-cell gene expression data across cell type, species, study, and other factors.
Methods: We 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 the data.
Results: The new portal provides quick visualization of over a million individual cells from vertebrate eye and body transcriptomes encompassing four species, 60 cell types, six ocular tissues, and 23 body tissues across 35 publications. To demonstrate the value of this unified pan-eye dataset, we replicated known neurogenic and cone macula markers in addition to proposing six new cone human region markers.
Conclusions: The PLAE web application offers the eye community a powerful and quick means to test hypotheses related to gene expression across a highly diverse, community-derived database.
Translational relevance: The PLAE resource enables any researcher or clinician to study and research gene expression patterning across a wide variety of curated ocular cell types with a responsive web app.