Darius P Schaub, Behnam Yousefi, Nico Kaiser, Robin Khatri, Victor G Puelles, Christian F Krebs, Ulf Panzer, Stefan Bonn
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引用次数: 0
Abstract
Motivation: The identification of biologically meaningful domains is a central step in the analysis of spatial transcriptomic data.
Results: Following Occam's razor, we show that a simple PCA-based algorithm for unsupervised 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.
Availability and implementation: The code is available at https://github.com/imsb-uke/nichepca.
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