Stanford Advisors


All Publications


  • Flexible and robust cell type annotation for highly multiplexed tissue images. bioRxiv : the preprint server for biology Sun, H., Yu, S., Casals, A. M., Bäckström, A., Lu, Y., Lindskog, C., Lundberg, E., Murphy, R. F. 2024

    Abstract

    Identifying cell types in highly multiplexed images is essential for understanding tissue spatial organization. Current cell type annotation methods often rely on extensive reference images and manual adjustments. In this work, we present a tool, Robust Image-Based Cell Annotator (RIBCA), that enables accurate, automated, unbiased, and fine-grained cell type annotation for images with a wide range of antibody panels, without requiring additional model training or human intervention. Our tool has successfully annotated over 1 million cells, revealing the spatial organization of various cell types across more than 40 different human tissues. It is open-source and features a modular design, allowing for easy extension to additional cell types.

    View details for DOI 10.1101/2024.09.12.612510

    View details for PubMedID 39345395

    View details for PubMedCentralID PMC11429614