691-FlashS: Detection for Scalable Spatial Transcriptomics
The paper introduces FlashS, a novel computational framework designed to identify spatially variable genes (SVGs) within massive spatial transcriptomics datasets. Current methods often struggle to balance statistical accuracy with the computational scalability required for million-cell atlases, frequently failing due to high memory demands or simplified models. FlashS overcomes these limitations by transforming spatial testing into the frequency domain using Random Fourier Features, which allows for the detection of complex, multi-scale patterns without the need for expensive distance…
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