Accurate cell type identification is a key and rate-limiting step in single cell data analysis.
Single cell references with comprehensive cell types, reproducible and functionally
validated cell identities, and common nomenclatures are much needed by the research community to optimize automated cell type annotation and facilitate data integration, sharing, and collaboration. In the present study, we developed a novel computational pipeline to utilize the LungMAP CellCards as a dictionary to consolidate single-cell transcriptomic datasets of 104 human lungs and 17 mouse lung samples to construct “LungMAP CellRef” and “LungMAP CellRef Seed” for both normal human and mouse lungs. “CellRef Seed” has an equivalent prediction power and produces consistent cell annotations to “CellRef” but improves computational efficiency and simplifies its utilization or fast automated cell type annotation and online visualization. These atlases incorporate 48 human and 40 mouse well-defined lung cell types catalogued from diverse anatomic locations and developmental time points. Using a total of 20 testing data from five independent studies, we demonstrated the utility of our CellRefs for automated cell type annotation analysis of both normal and diseased lungs. User-friendly web interfaces were developed to support easy access and maximal utilization of the LungMAP CellRefs. LungMAP CellRefs are freely available to the pulmonary research community through fast interactive web interfaces to facilitate hypothesis generation, research discovery, and identification of cell type alterations in disease conditions.
Published: September 22, 2023
Guo M., M.P. Morley, C. Jiang, Y. Wu, G. Li, Y. Du, and S. Zhao, et al. 2023.Guided construction of single cell reference for human and mouse lung.Nature Communications 14.PNNL-SA-181480.doi:10.1038/s41467-023-40173-5