Dimension-agnostic and granularity-based spatially variable gene identification
Published in bioRxiv (Cold Spring Harbor Laboratory), 2023
Identifying spatially variable genes (SVGs) is critical in linking molecular cell functions with tissue phenotypes. Spatially resolved transcriptomics captures cellular-level gene expression with corresponding spatial coordinates in two or three dimensions and can be used to infer SVGs effectively. However, current…
Recommended citation: Juexin Wang, Jinpu Li, Skyler T. Kramer, Li Su, Yuzhou Chang, Chunhui Xu, Qin Ma, Dong Xu. (2023). "Dimension-agnostic and granularity-based spatially variable gene identification" bioRxiv (Cold Spring Harbor Laboratory).
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