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bioRxiv · 10.1101/2024.07.29.605550

PCA-based spatial domain identification with state-of-the-art performance

Schaub, D. P.·Yousefi, B.·Kaiser, N.·Khatri, R.·Puelles, V. G.·Krebs, C. F.·Panzer, U.·Bonn, S.
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Abstract

The identification of biologically meaningful domains is a central step in the analysis of spatial transcriptomic data. Following Occams razor, we show that a simple PCA-based algorithm for spatial domain identification rivals the performance of ten competing state-of-the-art methods across six single-cell spatial transcriptomic datasets. Our reductionist approach, NichePCA, provides researchers with intuitive domain interpretation and excels in execution speed, robustness, and scalability.

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Schaub, D. P., Yousefi, B., Kaiser, N., Khatri, R., Puelles, V. G., Krebs, C. F., Panzer, U., Bonn, S.. 2024-07-30. PCA-based spatial domain identification with state-of-the-art performance. https://doi.org/10.1101/2024.07.29.605550

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