FlashS reveals multiscale spatial gene programs at atlas scale
Year: 2026
Type: preprint
Abstract: Spatial transcriptomics links gene expression to tissue architecture, but detecting spatially variable genes at atlas scale remains difficult because biologically relevant patterns are multiscale, sparse, and often non-parametric. Here we show that FlashS, a frequency-domain kernel test using random Fourier features, sparse sketching, and a kurtosis-corrected null, retains Gaussian-kernel flexibility at near-linear per-gene cost without permutation. Across 50 benchmark datasets spanning 9 spatial transcriptomics platforms, F lash S achieves the highest ranking accuracy among 14 compared methods while maintaining calibrated inference under simulation and full-atlas permutation. In human heart tissue, it recovers a mitochondrial biogenesis program that co-localizes with ventricular cardiomyocytes. On the Allen Brain MERFISH atlas containing 3.94 million cells, F lash S completes in minutes on a single workstation and separates biological signal from negative-control barcodes even when p-values saturate.
Authors: Chen Yang, Xianyang Zhang, Jun Chen
Institutions: Texas A&M University, Mayo Clinic
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
Award: G9000021690
OpenAlex ID: W7136553884