Benchmarking cell type annotation methods for 10x Xenium spatial transcriptomics data
Published in BMC Bioinformatics, 2025
We compared performance of five reference-based methods (SingleR, Azimuth, RCTD, scPred and scmapCell) with the marker-gene-based manual annotation method on an imaging-based Xenium data of human breast cancer. A practical workflow has been demonstrated for preparing a high-quality single-cell RNA reference, evaluating the accuracy, and estimating the running time for reference-based cell type annotation tools. SingleR was the best performing reference-based cell type annotation tool for the Xenium platform, being fast, accurate and easy to use, with results closely matching those of manual annotation.
Recommended citation: Cheng, J., Jin, X., Smyth, G. K., and Chen, Y. (2025). "Benchmarking cell type annotation methods for 10x Xenium spatial transcriptomics data." BMC Bioinformatics. 26(1), 22.
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